Category: 3. Business

Primary analysis data from the phase 3 ARES trial (NCT04769895) show that the microbiota-based therapeutic MaaT013 (Zervyteg) generated compelling efficacy signals and acceptable safety in patients with acute graft-vs-host disease with gastrointestinal involvement (GI-aGVHD) who are refractory to corticosteroids and ruxolitinib (Jakafi).¹ Results were presented by Florent Malard, MD, PhD, professor of Hematology at Saint Antoine Hospital and Sorbonne University, at the 67th American Society of Hematology (ASH) Annual Meeting and Exposition in Orlando, Florida.

As of the data cutoff on November 11, 2024, the study met its primary end point with a GI overall response rate (GI-ORR) of 62% (95% CI, 49%–74%) among 66 patients treated with MaaT013 on day 28 of treatment, significantly exceeding the historical control of 22% (P <.0001). The all-organ ORR was 64% (95% CI, 51%–75%). Notably, both GI and all-organ responses exhibited a similar average duration of response (DOR) of 6.4 months (95% CI, 4.8–8.0).

Furthermore, data describing key secondary end points revealed that responses were maintained through later time points. At day 56 and month 3, the GI-ORRs were 49% and 44%, respectively; likewise, all-organ ORRs were 48% and 44%. Responses across all time points showed exceptionally high rates of complete response and very good partial response.

Importantly, the deep and durable responses translated into promising survival benefits. A Kaplan-Meier graph displayed a separation of curves between responders and nonresponders beginning shortly after the first administration of MaaT013, widening substantially over the course of 1 year with responders maintaining a clear survival advantage over time. Median overall survival (OS) data were immature at the time of analysis, but the estimated probability of survival at 1 year was 54%, a clinically meaningful improvement for this patient population with historically poor clinical outcomes.

Safety and Tolerability

MaaT013’s safety profile was determined to be acceptable. There were 157 serious treatment-emergent adverse events (AEs) reported across 76% of patients, with the most common being escherichia sepsis, general physical health deterioration, and septic shock.

There was a total of 34 treatment-related AEs across 29% of patients, which mainly comprised various bacterial infections and GI disorders. Of these events, 7 were considered serious. There were 26 fatal AEs, with 1 event of septic shock determined to be related to MaaT013 by investigators.

About MaaT013 and the ARES Trial

The phase 3 ARES trial is a single-arm, multicenter, open-label trial in Europe investigating MaaT013, a pooled allogeneic fecal microbiotherapy, as salvage therapy in adult patients with refractory GI-aGVHD.² The primary end point of the trial is GI-ORR at day 28, assessed by an independent review committee (IRC); secondary end points include GI-ORR at day 56 and month 3, all-organ ORR at day 28, and DOR per IRC and investigator assessment, as well as OS. In the study, MaaT013 was administered as a rectal suspension as a 150-mL enema.

Patients were included if they had undergone allogeneic hematopoietic stem cell transplant, experienced an aGVHD episode with lower GI symptoms per MAGIC guidelines, and were resistant to systemic steroids and either resistant or intolerant to ruxolitinib. Key exclusion criteria included having active cytomegalovirus colitis, lines of aGVHD treatment other than steroids and ruxolitinib, hyperacute GVHD, and active uncontrolled infection.

Of the 66 total patients, the majority (77%) had aGVHD with involvement limited to the GI tract. Others had GI and skin involvement (17%), GI and liver involvement (3%), and involvement of all 3 organs (3%). Regarding the hypothesized mechanisms of action driving responses in the skin and liver, Malard offered some preliminary insights based on earlier research.

“So far, based on this study, we don’t have the translational data to investigate how this is working, but from the previous [phase 2] HERACLES study [NCT03225937], we already have some data on the fact that we have some systemic immunomodulatory effect of the drug, with some decrease in the proinflammatory cytokine at the systemic level, and also an increase in essential fatty acid… in the serum of the patient,” Malard explained in the question-and-answer session. “We are also going to evaluate in another study all the immune cell subsets, in particular Tregs and so on, to find if this is how it’s working.”

MaaT013 is currently under regulatory review by the EMA following submission of a marketing authorization application in June 2025, with a decision regarding approval anticipated in the second half of 2026.³ If approved, MaaT013 would become the first microbiome-based therapy for the treatment of this high-need disease.

DISCLOSURES: Malard declared receiving honoraria from Priothera, Jazz Pharmaceuticals, Therakos, Sanofi, Novartis, AstraZeneca, and MSD.

REFERENCES

1. Malard, F. MaaT013 for ruxolitinib-refractory acute graft-versus-host disease with gastrointestinal involvement: Results from the ARES phase III trial. Presented at: 67^th American Society of Hematology Annual Meeting and Exposition; December 6–9, 2025; Orlando, Florida. Abstract 817.‌

2. MaaT013 as salvage therapy in ruxolitinib-refractory GI-aGVHD patients (ARES). ClinicalTrials.gov. Updated October 17, 2024. Accessed December 6, 2025. https://clinicaltrials.gov/study/NCT04769895

3. November 3, 2025: Maat Pharma announces positive phase 3 results evaluating Xervyteg® (MaaT013) in acute graft-versus-host disease selected for oral presentation at ASH Congress 2025. News release. MaaT Pharma. November 3, 2025. Accessed December 7, 2025. https://tinyurl.com/su2wha2y

A quiet emergency is taking shape across America’s health care landscape, one defined not by new diseases, but by disappearing access. Pharmacy deserts are an escalating public health crisis in the US. Nearly 46% of US counties lack convenient pharmacy access, leaving over 16 million Americans without nearby options for essential medications. This access gap reflects a deeper inflection point: the traditional retail pharmacy model is no longer sustainable in many communities, pushing health care providers and technology partners to rethink how and where care is delivered.

As major retail pharmacy chains shutter thousands of stores, people in affected areas must travel over an hour to get prescriptions, vaccines, or basic health care needs. These closures are caused by a combination of financial pressure, industry consolidation, and changing consumer expectations, all of which creates a perfect storm that could leave millions of people behind.

This growing inaccessibility has a tangible cost. Medication nonadherence, often driven by lack of pharmacy access, adds $290 billion annually in avoidable healthcare expenses, including $100 billion in preventable hospitalizations.³ Rising drug costs and fragmented care coordination are now the leading forces behind declining adherence, intensifying disparities in chronic disease management and preventive care. When patients can’t access or refill prescriptions easily, the consequences ripple across the healthcare system, leading to poorer outcomes and higher costs.

Technology: Bridging the Accessibility and Care Gap

Digital innovation is essential to reversing this trend. Telepharmacy, mobile pharmacy apps, and artificial intelligence (AI)-enabled dispensing can dramatically extend reach, bringing pharmacists to patients virtually, 24/7. An analysis by Accenture shows telehealth visits are now 38 times higher than prepandemic levels, demonstrating that patients are ready for digital engagement.⁴

Meanwhile, 50% of OTC sales are projected to occur online within the next 3 to 4 years, and mobile pharmacy purchases are growing at a 19% compound annual growth rate through 2026. These shifts, along with home delivery, offer a blueprint for equitable access beyond physical locations. Yet technology alone isn’t the answer. Its impact depends on how providers integrate digital tools into care coordination and patient engagement models.

Reimagining Pharmacies as Frontline Care Hubs

For the pharmacies that remain, they must evolve from the last line of defense to the front line of care. Integrating pharmacies earlier in the care journey and connecting patients, payers, providers, and pharmacists creates a unified ecosystem that supports adherence and preventive health. Research shows that patients who receive pharmacy-based medical interventions have 3% higher medication adherence and 2.7% fewer emergency visits than those who do not.³

For providers, stepping directly into pharmacy access offers both necessity and opportunity. As value-based care expands, providers are increasingly accountable for outcomes that hinge on medication adherence. Direct partnerships, or even owned digital pharmacy models, allow them to close last-mile access gaps, reduce readmissions, and deliver continuous care outside traditional settings.

By expanding pharmacists’ roles to include services such as chronic disease monitoring, vaccinations, and medication therapy management, we can build stronger, value-based care models rooted in accessibility and trust.

Feeding the Appetite for Change

This type of change requires collaboration between providers, pharmacists, and technology innovators. Encouragingly, Accenture research shows nearly 80% of US adults say they are willing to share data within connected health systems to gain better access and coordinated experiences.⁵ The urgency is clear: Access is declining fastest where social determinants already strain health equity. Providers who act now can redefine their role not only as caregivers but also as enablers of consistent, affordable access to medication.

Ultimately, pharmacy deserts are a symptom of systemic fragmentation, and the cure lies in coordinated, technology-enabled care models that meet patients where they are. By transforming pharmacies into digital-first health access points, we can bridge gaps, improve outcomes, and build a healthier, more equitable future for all.

REFERENCES

1. Study finds 46 percent of US counties have pharmacy deserts. News release. National Community Pharmacists Association. August 28, 2024. Accessed December 8, 2025. https://www.ncpa.org/newsroom/qam/2024/08/28/study-finds-46-percent-us-counties-have-pharmacy-deserts

2. Nowosielski B. Pharmacy deserts prominent in areas of high social vulnerability. Drug Topics. August 23, 2024. Accessed December 8, 2025. https://www.drugtopics.com/view/pharmacy-deserts-prominent-in-areas-of-high-social-vulnerability

3. Kwan N. The impact of pharmacy deserts. US Pharm. 2024;49(4):32-36.

4. Bestesennyy O, Gilbert G, Harris A, Rost J. Telehealth: a quarter-trillion-dollar post-COVID-19 reality? McKinsey & Company. July 9, 2021. Accessed December 8, 2025. https://www.mckinsey.com/industries/healthcare/our-insights/telehealth-a-quarter-trillion-dollar-post-covid-19-reality

5. Accenture study finds growing demand for digital health services revolutionizing delivery models: patients, doctors + machines. News release. Accenture. March 6, 2018. Accessed December 8, 2025. https://newsroom.accenture.com/news/2018/accenture-study-finds-growing-demand-for-digital-health-services-revolutionizing-delivery-models-patients-doctors-machines

Adam Feuerstein is a senior writer and biotech columnist, reporting on the crossroads of drug development, business, Wall Street, and biotechnology. He is also a co-host of the weekly biotech podcast The Readout Loud and author of the newsletter Adam’s Biotech Scorecard. You can reach Adam on Signal at stataf.54.

ORLANDO, Fla. — Terns Pharmaceuticals reported an update Monday on its targeted leukemia drug that maintained and even boosted molecular response rates in advanced-stage patients. 

The study results, while still early, are likely to draw even more positive attention from investors who already view the Terns drug as a potential successor to a commercial blockbuster from Novartis. 

At 24 weeks, four escalating doses of the Terns drug, called TERN-701, achieved a major molecular response of 64% in patients with chronic myeloid leukemia, a slow-growing cancer that starts in myeloid cells. The 28 patients evaluable had already experienced treatment with a median of three drugs.

Consistent and robust efficacy demonstrated across bleed types, locations, and dose cohorts

The weekly dosing cohort achieved an estimated 87% reduction in annualized treated bleeding rate (ATBR)

Results validate potential as the first prophylactic therapy to address the heavy physical and psychosocial burden of Glanzmann thrombasthenia; Phase 3 registration study planned for 2026

CAMBRIDGE, Mass. and COPENHAGEN, Denmark, Dec. 8, 2025 /PRNewswire/ — Hemab Therapeutics, a clinical-stage biotechnology company developing novel prophylactic therapeutics for serious, underserved bleeding and thrombotic disorders, today announced positive results from its completed Phase 2 multiple ascending dose (MAD) portion of the CL-101 study of sutacimig for the prophylactic treatment of Glanzmann thrombasthenia (GT).

The data, presented today in an oral session at the 67th American Society of Hematology (ASH) Annual Meeting in Orlando, demonstrate clinically meaningful efficacy that was consistent across bleed locations, bleed types (spontaneous and traumatic), and dose cohorts evaluated. Based on these results, Hemab plans to advance sutacimig into a pivotal Phase 3 registration study in 2026.

“These Phase 2 results represent transformational potential for people living with Glanzmann thrombasthenia, who have waited a lifetime for a modern prophylactic treatment,” said Benny Sorensen, MD, PhD, Chief Executive Officer of Hemab. “The clinically meaningful reductions in bleeding demonstrated across this study provide compelling evidence that sutacimig could shift the treatment paradigm from reactive crisis management to prevention. We are moving forward with urgency to bring this therapy to patients who have been overlooked for far too long.”

“What stands out in these results is the reduction of the most severe bleeding events requiring intensive interventions,” said Paul Saultier, MD, PhD, Head of the French Platelet Reference Center, APHM Hospital de la Timone. “These are the bleeds that bring patients to the hospital and create the greatest burden. Combined with the reductions we saw across different bleed types and anatomical locations, these data suggest sutacimig could provide meaningful benefit for GT patients.”

Phase 2 Clinical Data Highlights: Hemab’s Phase 2 study of sutacimig (N=34) is intended to address a profound gap in care for GT as there are currently no effective prophylactic treatment options. Sutacimig was assessed at varying doses to determine the optimal regimen for Phase 3. Key findings include:

• Consistent and clinically meaningful reductions in bleeding: Sutacimig demonstrated robust and clinically meaningful reductions in ATBR across dose cohorts, with an approximate 50% reduction in mean ATBR in the overall efficacy population (N=31). The weekly dosing cohort achieved an estimated 87% reduction in ATBR (95% CI: 80%, 92%). Importantly, efficacy was consistent across all major bleed locations including nose, gum/mouth, and gastrointestinal sites, and demonstrated robust activity against both traumatic and spontaneous bleeding events.
• Reduction of bleeds requiring high intensity treatment: Participants experienced a 100% reduction in mean ATBR of bleeding events requiring high intensity treatment (defined as those requiring recombinant factor VIIa, platelet transfusions, plasma, cryoprecipitate, or medical procedures) during the treatment period. This represents a meaningful reduction of the most clinically consequential acute bleeding events.
• Dosing schedule optimization: Analyses indicate that weekly dosing provides consistent exposure across the dosing interval, resulting in optimal clinical response.
• Safety and tolerability: Overall sutacimig was well tolerated. Adverse events were primarily mild to moderate and either non-specific or typical for patients with GT, with a single related serious adverse event (grade 2 DVT) occurring at the highest dose level (0.9 mg/kg). Anti-drug antibodies impacting PK/PD were observed in five participants; however, titers resolved in one participant with continued dosing, and no associated safety events were reported.
• Retention: Underscoring the perceived benefit, 82% of participants elected to enter the ongoing long-term extension study.

Presentation Details

• Title: Sutacimig, a Novel Bispecific Antibody for Prophylactic Treatment of Glanzmann Thrombasthenia: Analysis of a Phase 2 Study
• Session: OCCC – W304EFGH
• Presenter: Paul Saultier, MD, PhD, APHM Hospital de la Timone, France

^{*Data as of July 1, 2025.}

About Glanzmann Thrombasthenia
Glanzmann thrombasthenia (GT) is a severe bleeding disorder marked by debilitating, sometimes life-threatening bleeding episodes. Results from an international Glanzmann’s 360 (GT360) natural history study revealed the substantial burden of this disease: 88% of the 117 participants reported at least one bleed in the previous week, with 34% of those bleeds requiring medical treatment. These bleeding episodes significantly impact patients’ mental health and quality of life, with 67% reporting low mood, 52% reporting emotional problems, and 46% experiencing social isolation. Additionally, 81% of participants reported missing school or work due to bruising or bleeding. To date, there are no effective prophylactic treatment options for GT.

About Sutacimig (formerly HMB-001)
Sutacimig is a subcutaneously administered bispecific antibody that binds and stabilizes endogenous Factor VIIa with one antibody arm and binds to TLT-1 on activated platelets with the other arm. This mechanism allows for the accumulation of endogenous Factor VIIa in the body and recruitment of Factor VIIa directly to the surface of the activated platelets, where it facilitates hemostatic plug formation. Sutacimig is designed to be a first-in-class prophylactic treatment for Glanzmann thrombasthenia (GT) with the potential to treat other debilitating bleeding disorders. The U.S. Food and Drug Administration granted Fast Track Designation and Orphan Drug Designation to sutacimig for the treatment of GT while the UK Medicines and Healthcare products Regulatory Agency has awarded it designation under the Innovative Licensing and Access Pathway (ILAP). For more information, please visit clinicaltrials.gov (NCT06211634).

About Hemab Therapeutics
Hemab is a multiple clinical-asset biotechnology company developing novel prophylactic therapeutics for serious, underserved bleeding and thrombotic disorders. Based in Cambridge, MA, and Copenhagen, Denmark, Hemab is progressing a pipeline of innovative therapeutic solutions, leveraging a variety of cutting-edge technologies and approaches to transform the treatment paradigm for patients with high unmet need. The company’s strategic guidance, Hemab 1-2-5™, targets building a pipeline of development programs to deliver long-awaited innovation for people with high unmet need diseases like Glanzmann thrombasthenia, Factor VII Deficiency, Von Willebrand Disease, and others. Learn more at hemab.com. Follow us on LinkedIn, Facebook, Instagram, and X.

Media:
Deerfield
Peg Rusconi
[email protected]

Investors:
Hemab Therapeutics
Mads Behrndt
[email protected]

SOURCE Hemab Therapeutics

The news: L’Oréal is doubling its stake in cosmetic injectables company Galderma to 20%, the company said, as it looks to expand in the fast-growing aesthetics market and support growth amid global headwinds.

The big picture: While some competitors retrench, L’Oréal is pursuing acquisitions in beauty categories with the strongest growth potential.

• The company’s largest deal so far this year, its €4 billion ($4.3 billion) purchase of Kering’s beauty business, will position it as one of the world’s top makers of luxury fragrances, a category that is a driving force behind beauty sales growth.
• L’Oréal also acquired luxury haircare brand Color Wow earlier this year, which will help strengthen its dominance in its second-fastest-growing segment after fragrance.
• Other notable recent acquisitions include a majority stake in premium skincare brand Medik8, as well as K-beauty brand Dr.G.
• The company is also preparing a bid for Armani Beauty, which, if successful, would give it a larger share of the luxury cosmetics market.

What it means: L’Oréal’s acquisition strategy could reshape the beauty industry—mainly at the expense of players like Coty and Shiseido, which are reorganizing their businesses amid slumping demand for their portfolios.

At the same time, the company’s moves reflect the shifts in consumer beauty spending. Resilient demand for self-care, wellness, and premium products is fueling growth in fragrances and haircare, while K-beauty is gaining traction as consumers search for affordable and effective skincare products.

This content is part of EMARKETER’s subscription Briefings, where we pair daily updates with data and analysis from forecasts and research reports. Our Briefings prepare you to start your day informed, to provide critical insights in an important meeting, and to understand the context of what’s happening in your industry. Non-clients can click here to get a demo of our full platform and coverage.

INDIANAPOLIS, Dec. 8, 2025 /PRNewswire/ — The board of directors of Eli Lilly and Company (NYSE: LLY) has declared a dividend for the first quarter of 2026 of $1.73 per share on outstanding common stock.

The dividend is payable on March 10, 2026, to shareholders of record at the close of business on February 13, 2026.

About Lilly
Lilly is a medicine company turning science into healing to make life better for people around the world. We’ve been pioneering life-changing discoveries for nearly 150 years, and today our medicines help tens of millions of people across the globe. Harnessing the power of biotechnology, chemistry and genetic medicine, our scientists are urgently advancing new discoveries to solve some of the world’s most significant health challenges: redefining diabetes care; treating obesity and curtailing its most devastating long-term effects; advancing the fight against Alzheimer’s disease; providing solutions to some of the most debilitating immune system disorders; and transforming the most difficult-to-treat cancers into manageable diseases. With each step toward a healthier world, we’re motivated by one thing: making life better for millions more people. That includes delivering innovative clinical trials that reflect the diversity of our world and working to ensure our medicines are accessible and affordable. To learn more, visit Lilly.com and Lilly.com/news, or follow us on Facebook, Instagram, and LinkedIn. F-LLY

Cautionary Statement Regarding Forward-Looking Statements
This press release contains forward-looking statements (as that term is defined in the Private Securities Litigation Reform Act of 1995) about expected dividend payments and reflects Lilly’s current beliefs and expectations. However, there are significant risks and uncertainties in pharmaceutical research and development, as well as in business development activities and capital allocation strategies related to the company’s business and actual results may differ materially due to various factors. For further discussion of risks and uncertainties relevant to Lilly’s business that could cause actual results to differ from Lilly’s expectations, see Lilly’s Form 10-K and Form 10-Q filings with the United States Securities and Exchange Commission. Except as required by law, Lilly undertakes no duty to update forward-looking statements to reflect events after the date of this release.

SOURCE Eli Lilly and Company

Here, we engineered BOAS that included tandemly linked, antigenically distinct HA heads as a single construct. This platform allows a mixing-and-matching of up to eight distinct HA heads from both influenza A and B viruses. Furthermore, we showed that the order and number of HA heads can vary without losing reactivity to conformation-specific mAbs in vitro, highlighting the flexibility of this platform. Mice immunized with BOAS had comparable serum reactivity to each individual component though relative binding and neutralization titers varied between immunogens; this is likely a consequence of length and/or composition. Further oligomerization for increased multivalent display was accomplished by conjugating two 4mer BOAS inclusive of eight distinct HA heads to a ferritin nanoparticle via SpyTag/SpyCatcher ligation. Similar to the BOAS, these conjugated nanoparticles elicited similar titers to all eight HA components and could neutralize matched viruses.

Thus, tandemly linking HA heads is a robust method for displaying multiple influenza HA subtypes in a single protein-based immunogen. Binding titers were elicited to all components present in the immunogen, and there was no significant correlation between HA position within the BOAS (i.e. internal or terminal) and immunogenicity. However, the relative immunogenicity of each HA varied despite equimolar display of each HA subtype. There were qualitatively immunodominant HAs, notably H4 and H9, and these were relatively consistent across BOAS in which they were a component; this effect was reduced in the mix cohort. Further studies using the modularity of the BOAS could further deconvolute relative immunodominances of HA subtypes.

Despite similar binding titers across multiple BOAS lengths, expression levels and neutralization titers were quite variable. While all 3mer to 8mer BOAS could be overexpressed, expression inversely correlated with overall length. To mitigate this, multiple BOAS (e.g. two 4mers) or conjugation to protein-based nanoparticles, as was done here, could be used to ensure coverage of each desired HA subtype. Furthermore, neutralization titers were quite variable across different BOAS lengths despite similar binding titers. This may be related to multiple factors, including homology, stability, and accessibility of neutralizing epitopes for different BOAS lengths. Notably, for longer BOAS, we observed degradation following longer term storage at 4° C, which may reflect their overall stability. Studies manipulating BOAS composition at intermediate lengths could optimize neutralizing responses to particular influenzas of interest.

Based on the immunogenicity of the various BOAS and their ability to elicit neutralizing responses, it may not be necessary to maximize the number of HA heads into a single immunogen. Indeed, it qualitatively appears that the intermediate 4-, 5-, and 6mer BOAS were the most immunogenic and this length may be sufficient to effectively engage and crosslink B cell receptors (BCRs) for potent stimulation. These BOAS also had similar or improved binding cross-reactivity to mismatched HAs as compared to longer 7- or 8mer BOAS. Notably, the 3mer BOAS elicited detectable cross-reactive binding titers to H4 and H5 mismatched HAs. This observed cross-reactivity could be due to sequence conservation between the HAs, as H3 and H4 share ~51% sequence identity, and H1 and H2 share ~46% and~62% overall sequence identity with H5, respectively (Figure 4—figure supplement 1). Additionally, the degree of surface conservation decreased considerably beyond the 5mer as more antigenically distinct HAs were added to the BOAS. These data suggest that both antigenic distance between HA components and BOAS length play a key role in eliciting cross-reactive antibody responses, and further studies are necessary to optimize BOAS valency and antigenic distance for a desired humoral response.

Potential enrichment of serum antibodies targeting the conserved RBS and TI epitopes may also be contributing to observed cross-reactivity. Both epitopes are relatively conserved across all BOAS (Figure 4C), and the two BOAS showing the most cross-reactivity, the 3mer and 5mer, elicit a significant portion of the serum response toward both RBS and TI epitopes as determined via a serum competition assay with available epitope-directed mAbs (Figure 4B). Notably, this proportion is approximate, as at the time of reporting, mAbs that bind the receptor binding site of all components were not available. RBS-directed mAbs to the H4 and H9 components were not available, and the RBS-directed antibodies used targeting the other HA components have different footprints around the periphery of the RBS. Additionally, there are currently no reported influenza B TI-directed mAbs in the literature. Therefore, this may be an underestimate of the serum proportion focused on the conserved RBS and TI epitopes. Isolated TI-directed mAbs, in particular, can engage more than nine unique subtypes across both group 1 and 2 influenzas (McCarthy et al., 2021; Watanabe et al., 2019), and our monomeric head-based BOAS immunogens have the otherwise occluded TI epitope exposed (McCarthy et al., 2021; Bangaru et al., 2019; Watanabe et al., 2019). Furthermore, we have previously shown that this TI epitope, when exposed, is immunodominant in the murine model (Bajic et al., 2019). Further studies with different combinations of HAs could aid in understanding how length and composition influences epitope focusing. For example, a BOAS design with a cluster of group 1 HAs followed by a cluster of group 2 HAs, rather than our roughly alternating pattern could influence which HAs are in close proximity to one other or could be potentially shielded in certain conformations and thus could affect antigenicity. Combining the BOAS platform with other immune-focusing approaches (Dosey et al., 2023), such as hyperglycosylation (Bajic et al., 2019; Thornlow et al., 2021; Ingale et al., 2014; Eggink et al., 2014) or resurfacing (Bajic et al., 2020; Hai et al., 2012) could enhance cross-reactive responses. Additionally, modifying linker spacing and rigidity can also be used as a mechanism to enhance BCR cross-linking and thus enhance cross-reactive B cell activation and elicitation (Veneziano et al., 2020).

BOAS can be further multimerized via conjugation to a surface of a NP. Interestingly, this only had a marginal effect on immunogenicity. The BOAS NP elicited titers of ~10⁵ (Figure 6B), whereas the best BOAS alone reached an order of magnitude greater (Figure 3C). This appears in contrast with other studies where attaching an antigen to a NP scaffold enhanced immunogenicity and neutralization potency (Kanekiyo et al., 2013; Jardine et al., 2013; Tokatlian et al., 2019; Kato et al., 2020; Marcandalli et al., 2019). One recent example designed quartets of antigenically distinct SARS-like betacoronavirus receptor binding domains (RBDs) coupled to an mi3-VLP scaffold via a similar SpyTag-SpyCatcher system and showed increased binding and neutralization titers following conjugation to the NP compared to quartet alone (Hills et al., 2024). This discrepancy may be in part due to the larger mi3 NP (Bruun et al., 2018) which displays 60 copies of the antigen rather than the 24 copies displayed on the ferritin NP used in this study. It is also possible that the difference in immunogenicity could arise from the increased molecular weight of the BOAS NP immunogen compared to the BOAS alone, leading to a difference in moles of BOAS antigen in each cohort. However, due to the large size of the BOAS, the addition of the ferritin NP does not add a large amount of mass. 20 µg of BOAS NP or an 8mer BOAS equates to ~64 and ~83 µmoles of each HA component, respectively. This ~30% greater amount of HA in the 8mer BOAS, however, does not account for the observed difference in serum binding titers. Nevertheless, HA-specific responses were similar whether the BOAS were conjugated to the nanoparticle or not, indicating that HA proximity to the NP surface did not impact responses to each component. This observation is consistent with betacoronavirus quartet NPs as well. Additionally, BOAS conjugation to the NP significantly reduced the scaffold-directed response. The addition of the large BOAS projections to the NP surface likely masked the immunogenic scaffold epitopes (Kraft et al., 2022).

Collectively, this study demonstrates the versatility of the BOAS platform to present multiple HA subtypes as a single immunogen. This ‘plug-and-play’ approach can readily exchange HAs to elicit desired immune responses. BOAS are potentially advantageous over other multivalent display platforms, such as protein-based NPs, which can produce off-target responses due to their inherent immunogenicity (Kanekiyo et al., 2013). Furthermore, when genetic fusions of the antigen to nanoparticles is not possible, SpyTag-SpyCatcher (or another suitable conjugation approach) must be used, further contributing to scaffold-specific responses as well as additional multi-step manufacturing and purification challenges. Not only does our BOAS platform circumvent these potential caveats, but because this is a single polypeptide chain, this immunogen could readily be formulated as an mRNA lipid nanoparticle (LNP) (Chaudhary et al., 2021). The BOAS platform forms the basis for next-generation influenza vaccines and can more broadly be readily adapted to other viral antigens.

Designing novel target molecules by integrating the topological, chemical, and physical attributes of protein cavities necessitates advanced neural networks. While existing approaches like Bicyclic Generative Adversarial Networks (BicycleGANs) (Skalic et al., 2019) and Recurrent Neural Networks (RNNs) (Xu et al., 2021) have demonstrated potential, end-to-end standalone tools for GPCR-specific ligand design remain scarce. To address this, we developed the Gcoupler and provided it to the community as a Python Package and a Docker image. Gcoupler adopts an integrative approach utilizing structure-based, cavity-dependent de novo ligand design, robust statistical methods, and highly powerful Graph Neural Networks. Gcoupler consists of four interconnected modules, that is, Synthesizer, Authenticator, Generator, and BioRanker, that collectively impart a smoother, user-friendly, and minimalistic experience for the end-to-end de novo ligand design.

Synthesizer, the first module of Gcoupler, takes a protein structure as input in Protein Data Bank (PDB) format and identifies putative cavities across the protein surface, providing users with the flexibility to select cavities based on druggability scores or user-supplied critical residues. Since cavity-dependent molecule generation mainly depends on the chemical composition and geometric constraints of the cavity, it is, therefore, indispensable to select the cavity for the downstream steps considering its chemical nature (hydrophobicity/hydrophilicity) and functional relevance (proximity to the active site or residue composition), among others. Accounting for these, Gcoupler offers flexibility to the users to select either of its predicted cavities based on the user-supplied critical residue or by user-supplied cavity information (amino acids) using third-party software (e.g., Pocketome) (Hedderich et al., 2022). To enhance user experience, Gcoupler computes and outputs all identified cavities along with their druggability scores using LigBuilder’s V3 (Yuan et al., 2020) cavity module. Briefly, these druggability scores consider solvent accessibility, cavity exposure or burial, and detected pharmacophores and cavities, which are further prioritized based on this score. Post-cavity selection, the Synthesizer module generates cavity-specific ligands influenced by topology and pharmacophores, outputting SMILES, cavity coordinates, and other requisite files to downstream modules for further steps (Figure 1a). The chemical composition of the in silico synthesized ligands by the Synthesizer module is influenced by the cavity topology (3D) and its composition (pharmacophores). Noteworthy, the Synthesizer module of Gcoupler employs LigBuilder V3 (Yuan et al., 2020), which utilizes the genetic algorithm for the in silico ligand synthesis. Notably, the fragment library of LigBuilder, comprising 177 distinct molecular fragments in Mol2 format, allows the selection of multiple seed structures and extensions that best complement the cavity pharmacophores throughout multiple iterative runs. For each run, once a seed structure is confirmed, Gcoupler employs a hybrid approach of the Growing and Linking modes of the LigBuilder build module, enabling the stepwise addition of small fragments to the seed structure within the binding pocket of the target GPCR to build synthetic ligands. Gcoupler generates 500 unique molecules by default, though it can also be user-defined. The Synthesizer module of Gcoupler enhances LigBuilder V3 practical applicability through automation, dynamic adaptability, and abstraction. This allows for more efficient and targeted ligand generation, even in challenging design scenarios for GPCR ligand design. However, it lacks user-defined library screening, proposes synthetically challenging molecules, and often requires post-processing to isolate High-Affinity Binders () from a broad affinity range of synthetically designed compounds.

To address this limitation, a second module was added to Gcoupler, termed Authenticator. This module processes output files from the Synthesizer module, conducting downstream validation steps and preparing results for constructing deep learning-based classification models (third module). The Authenticator requires input protein 3D structure in PDB format, cavity coordinates, and all silico-generated molecules from the Synthesizer module. Authenticator utilizes this information to further segregate the synthesized compounds into HABs and Low-Affinity Binders (LABs) by leveraging a structure-based virtual screening approach (AutoDock Vina) (Trott and Olson, 2010) and statistically backed hypothesis testing for distribution comparisons (Figure 1a). The Authenticator module outputs the free binding energies of all the generated compounds, which further segregates the compounds into HABs and LABs by the statistical submodule while ensuring the optimal binding energy threshold and class balance. Of note, the Authenticator is also capable of leveraging the Empirical Cumulative Distribution Function (ECDF) for binding energy distribution comparisons of HABs and LABs and performs the Kolmogorov–Smirnov test (Berger and Zhou, 2014), Epps–Singleton test (Goerg and Kaiser, 2009), and Anderson–Darling test (Engmann and Cousineau, 2011) for hypothesis testing. This expanded array of statistical tests allows users to employ methodologies that best suit their data distribution characteristics, ensuring robust and comprehensive analyses. Moreover, the Authenticator module incorporates a unique feature for decoy synthesis using HABs. This functionality enables the generation of a negative dataset in scenarios where the Synthesizer module fails to produce an optimal number of LABs. By synthesizing decoys from HABs, users can effectively balance their datasets, enhancing the reliability of downstream analyses. Lastly, the Authenticator module also accommodates user-supplied negative datasets as an alternative to LABs (Mysinger et al., 2012). This feature provides users with the flexibility to incorporate external data sources, enabling robust prediction model building by the subsequent Generator module.

The Generator, the third module, employs state-of-the-art GNN models such as Graph Convolution Model (GCM), Graph Convolution Network (GCN), Attentive FP (AFP), and Graph Attention Network (GAT) to construct predictive classifiers using Authenticator-informed classes. These GNN algorithms are tailored to extract features from the graph structure of the compounds generated by the Synthesizer and apply them to the classification task by leveraging Authenticator-informed class information. For instance, the GCM assimilates features by analyzing neighboring nodes, while the GCN extracts features through a convolutional process. The AFP model focuses attention on specific graph segments, and the GAT employs attention mechanisms to learn node representations. By default, Generator tests all four models using standard hyperparameters provided by the DeepChem framework (https://deepchem.io/), offering a baseline performance comparison across architectures. This includes pre-defined choices for node features, edge attributes, message-passing layers, pooling strategies, activation functions, and dropout values, ensuring reproducibility and consistency. All models are trained with binary cross-entropy loss and support default settings for early stopping, learning rate, and batch standardization where applicable. Gcoupler provides off-the-shelf hyperparameter tuning to ensure adequate training, which is essential for optimizing model performance. After selecting the best parameters and classification algorithm, Gcoupler further ensures the mitigation of overfitting and provides a more precise estimate of model performance through k-fold cross-validation. Notably, by default, Gcoupler employs threefold cross-validation, but users can adjust this parameter.

Finally, BioRanker, the last module, prioritizes ligands through statistical and bioactivity-based tools. The first level ranking offered by BioRanker is composed of a statistical tool that encompasses two distinct algorithms, namely G-means and Youden’s J statistics, to assist users in identifying the optimal probability threshold, thereby refining the selection of high-confidence hit compounds (Figure 1—figure supplement 1a). Additionally, bioactivity embeddings computed via Signaturizer (Bertoni et al., 2021) enable multi-activity-based ranking using a modified PageRank algorithm. Briefly, the bioactivity descriptors of the predicted compounds are projected onto various biological activity spaces, including Chemistry, Targets, Networks, Cells, and Clinics, by performing pairwise cosine similarity comparisons with HABs. The PageRank algorithm is then applied for activity-specific ranking and supports multi-activity-based ranking for sequential screening based on user-defined biological properties. BioRanker also offers flexibility through customizable probability thresholds, enabling stringent or relaxed selection of compounds. Users can also input SMILES representations for direct screening, bypassing prediction probabilities. Taken together, Gcoupler is a versatile platform supporting user-defined inputs, third-party tools for cavity selection, and customizable statistical analyses, enhancing its adaptability for diverse ligand design and screening tasks. This integrated framework streamlines cavity-specific ligand design, screening, and ranking, providing a comprehensive solution for GPCR-targeted drug discovery.

To evaluate Gcoupler’s performance, we tested its modules across five GPCRs (AA2AR, ADRB1, ADRB2, CXCR4, and DRD3) using experimentally validated ligands and matched decoys from the DUD-E dataset (Mysinger et al., 2012). The DUD-E datasets contain five GPCRs alongside information about their cavity coordinates, positive ligands, and decoys (https://dude.docking.org/subsets/gpcr). We used these five GPCRs as independent samples to evaluate different modules and sub-modules of Gcoupler. We first checked whether the cavity search algorithm of Synthesizer could accurately detect a given orthosteric ligand-binding site for a GPCR. Gcoupler accurately identified orthosteric ligand-binding sites and additional allosteric cavities across all targets, validating its de novo cavity detection algorithm (Figure 1—figure supplement 1b). We next asked whether Gcoupler could also synthesize molecules similar to the reported ligands for respective orthosteric sites based on the cavity’s physical, chemical, and geometric properties. For orthosteric sites, the Synthesizer module generated ~500 compounds per GPCR. Subsequently, as per the Gcoupler default workflow, the Authenticator module conducted a virtual screening of these newly synthesized compounds, segregating them into HABs and LABs. Although the Authenticator module provides flexibility in selecting an optimal threshold to distinguish HAB and LAB, we chose the default cutoff of –7 kcal/mol for AA2AR, CXCR4, and DRD3. For ADRB1 and ADRB2, we selected a threshold of –8 kcal/mol to minimize overlap in distributions and thus avoid class imbalance, a critical parameter that could influence the downstream model generation using the Generator module (Figure 1—figure supplement 1c). Statistical validation confirmed significant separation between these groups (p < 0.0001), enabling the Generator module to construct graph-based classification models with high values of AUC–ROC (>0.95), sensitivity, and specificity (Figure 1b, c, Figure 1—figure supplement 1d, e). These models reliably distinguished ligands from decoys, demonstrating Gcoupler’s accuracy in identifying high-affinity ligands.

In addition to evaluating Gcoupler’s performance for the orthosteric sites of GPCRs, we also validated its capability to identify allosteric sites and their corresponding ligands. In this case, we first gathered information about the experimentally validated GPCR–ligand complexes sourced from the PDB database. We chose three GPCR–ligand complexes (β2AR-Cmpd-15PA, CCR2-CCR2-RA-[R], and CCR9-Vercirnon) from the PDB (Shen et al., 2023). We removed the ligands from the PDB files and executed the standard Gcoupler workflow with default parameters. Gcoupler successfully identified allosteric binding sites and generated classification models for synthetic compounds with consistently high AUC–ROC values (>0.95) (Figure 1d, Figure 1—figure supplement 2a–c). This high level of accuracy indicates the robustness of Gcoupler’s algorithms in distinguishing between true positives (allosteric ligands) and true negatives (non-binders). Projection of experimentally validated ligands onto these models further confirmed their predictive accuracy (Figure 1e), underscoring Gcoupler’s robustness and versatility for orthosteric and allosteric ligand discovery.

Next, to evaluate the efficiency of Gcoupler, we compared its run time with the biophysics-based gold standard molecular docking (AutoDock) (Morris et al., 2009). To address the runtime efficiency, we first utilized the ChEMBL31 database (Gaulton et al., 2012) to identify GPCRs with the highest number of reported experimentally validated agonists. We selected the alpha-1A adrenergic receptor (ADRA1A) since it qualifies for this criterion and contains 993 agonists (Figure 1—figure supplement 3a, b). Methodologically, we followed the conventional steps of AutoDock Tools for molecular docking while keeping track of execution time for each step throughout the entire process until completion (Figure 1—figure supplement 3a, c). In parallel, we applied the same timestamp procedure for Gcoupler, including its individual module sub-functions (Figure 1—figure supplement 3a–d). Gcoupler was 13.5 times faster, leveraging its deep learning-based Generator module and AutoDock Vina’s efficiency. Both methods provided comparable predictions for active compounds, demonstrating Gcoupler’s speed and accuracy, making it ideal for large-scale ligand design and drug discovery (Figure 1—figure supplement 3e–h).

Finally, we used Gcoupler to evaluate the ligand space conservation (functional conservation) of the GPCR–Gα interface. Specifically, we aimed to explore the possibility of direct small molecule binding to the GPCR–Gα interface to modulate downstream signaling pathways. We analyzed multiple human GPCR–Gα complexes from the PDB (Figure 1f, Supplementary file 1), identified conserved motifs (DRY, CWxL, and NPxxY) and binding pockets through sequence and structural analyses (Figure 1g). To determine the topological similarity of the GPCR–Gα-protein interface, we undertook a detailed structural analysis across a wide array of GPCR–Gα-protein complexes. This analysis involved identifying and extracting the cavities present within each complex. By focusing on these critical regions, we aimed to assess the degree of structural conservation and quantify it through normalized root mean square deviation (RMSD) values. Specifically, the normalized RMSD values, which provide a measure of the average distance between atoms of superimposed proteins, indicated a high degree of similarity. The mean RMSD value was found to be 1.47 Å, while the median RMSD value was even lower at 0.86 Å. These values suggest that the overall topology of the GPCR–Gα interface is well conserved across different complexes, highlighting the robustness of this interaction site (Figure 1h–j, Figure 1—figure supplement 3i–k, Supplementary file 2). Finally, to test whether this topological and sequence conservation also impacts the ligand profiles that could potentially bind to this interface, we performed the Gcoupler workflow on all 66 GPCRs and synthesized ~50 unique ligands per GPCR (Figure 1h). We next computed and compared the physicochemical properties (calculated using Mordred; Moriwaki et al., 2018) of these synthesized ligands and observed high cosine similarity, which further supports the functional conservation of the GPCR–Gα interface (Figure 1h, k, Figure 1—figure supplement 3l, Supplementary file 3). In summary, we used Gcoupler to systematically evaluate and analyze the ligand profiles of the GPCR–Gα-protein interface and observed a higher degree of sequence, topological, and functional conservation.

Activewear brand Sweaty Betty has become involved in a new dispute over advertising slogans, which a period underwear company claims were copied.

Kelly Newton said Sweaty Betty’s use of two taglines that were very similar to her firm Nixi Body’s “seemed a little off”, and while she could not get them trademarked she felt Sweaty Betty was “taking from” other female founders.

Sweaty Betty said the “No ifs. Just butt.” line had been used by many brands and influencers, but also said it was reviewing all its marketing campaigns.

Ms Newton said she was speaking out after seeing personal trainer Georgina Cox reveal Sweaty Betty had offered her a settlement over a disputed slogan.

Ms Newton, who co-founded Nixi Body in 2019, said the company has advertised its leak-proof period underwear with the lines “Keeping you moving through menstruation, motherhood and menopause” and “No leaks. No ifs. Just butts.” for years.

But late last year a friend alerted her to a Sweaty Betty ad for its femtech range of leak-resistant and maternity leggings with the tagline “Keeping you moving through menstruation, maternity and menopause”.

At first, Ms Newton thought it could have been a coincidence, and said she was annoyed but did not feel there was anything she could do.

That tagline has since been changed on the Sweaty Betty website to “Menstruation. Maternity. Menopause. Together we’re raising the bar for every woman, for any life stage.”

Then, earlier this year, she noticed Sweaty Betty was running a campaign with the line “No ifs. Just butt.”

“I thought ‘oh hang on a second’,” Ms Newton told the BBC.

Again, Ms Newton said she didn’t reach out. She said she had tried to get the “Keeping you moving through menstruation, motherhood and menopause” line trademarked but was unable to do so, and said she knew that legally she had little recourse.

“Legally they were within their rights to use these words, but they’re words that we’ve used for quite a few years.”

It was personal trainer Ms Cox sharing her story about dealing with the brand that made her want to speak out, Ms Newton said.

Last month Ms Cox revealed that Sweaty Betty had offered her £4,000 in exchange for confidentiality over the use of the phrase “Wear The Damn Shorts” that she claims was used without crediting her in its latest campaigns.

She told the BBC she came up with the slogan alongside her sister in 2020 and it quickly went viral. In 2023, Sweaty Betty approached her to use it in a campaign and paid her £3,500 to do so.

She was also paid for another campaign using it in 2024, but was not approached about it for this year.

Ms Newton said she felt compelled to speak out about her experience after talking to Ms Cox, because she was not the only person affected.

“Your tagline can’t be empowering all women when actually all you’re doing is taking from them,” she said, adding that she was not seeking compensation but rather for Sweaty Betty to be accountable.

“It just feels like for me all the slogans I’m seeing are coming from other female founders.

“I just want them to do the right thing and just morally acknowledging what they’ve done isn’t great and to do better really.”

Sweaty Betty said it chose words “to empower women through fitness” to advertise its femtech range, something many brands try to do, which “sometimes… means the language used by different brands aligns”.

“We have been using the phrase for over a year and Nixi has not been in touch with us about our use of it. The phrase is used by many brands in various forms and that is why no individual or brand can claim exclusive rights to it or trademark it,” the company said in a statement.

“It is never our intent to take credit for the work or creativity of others, particularly from trailblazing women, and we have reached out to Nixi Body directly to convey this. We have also been undertaking a review of all our campaigns and marketing language to fully understand the origins of the phrases we use and will continue to do this.

“We note that such a review was conducted with respect to the ‘Wear the Damn Shorts’ phrase and its origins date back to at least as early as 2019, before either Ms Cox or Sweaty Betty first used the phrase. We continue to work towards a resolution with Ms Cox, as has always been our objective, however this dispute remains ongoing.”

Introduction

Children aged 0-18 years with life-limiting or life-threatening conditions or terminal illnesses could benefit from pediatric palliative care (PPC) []. Life-limiting conditions include children where a premature death is expected due to lack of a reasonable cure [,]. Life-threatening conditions include conditions such as congenital anomalies, cancer, and neurological conditions where there is a high probability of premature death, but where there remains a chance of survival into adulthood [,]. The proportion of children in need of PPC is increasing across the world []. PPC is defined as “the active total care of the child’s body, mind and spirit, and [this] also involves giving support to the family” []. PPC aims to optimize quality of life and care for these children and to address their wishes, choices, and needs and those of their families [,]. However, such children experience burdensome symptoms, concerns, and health outcomes that interact and occur during their illness trajectories [,]. PPC should be introduced at the time of diagnosis and provided throughout children’s lives [,,].

Many families with children who need PPC tend to stay at home to preserve a sense of normalcy [,]. However, such families report a lack of access to out-of-hours support for addressing complex care needs. They also lack educational support and resources related to symptom management and their caregiving roles []; for example, how to manage symptoms to keep their children comfortable and free from pain and discomfort []. Similarly, families need to monitor their children’s symptoms, physical conditions, and well-being so that they can intervene when necessary []. Health care professionals (HCPs) emphasize that providing support for children’s needs can strengthen parents’ ability to manage their children’s pain and discomfort, thereby helping children and families articulate their experiences and describe the physical changes the children experience []. Families frequently need to contact hospitals for consultations or assistance, initiate contact with community health services, and plan and coordinate care [,]. However, they may feel powerless, helpless, and isolated [].

The use of health technology for home-based PPC may be a way to enhance communication between home-based families and HCPs to support the needs of children and their families. We define health technology as information and communication technologies broadly used to enhance person-centered care, including telehealth, telemedicine, digital health, mobile health, and eHealth []. Health technology can benefit children and their families in home-based PPC by supporting them in communicating with HCPs, especially in discussing care goals and caregiver well-being []. A retrospective chart review revealed that children with cancer were usually seen in person, while children with neurologic diagnoses, medical technology dependence, and a higher number of complex chronic conditions were more often monitored using health technology. However, health outcomes, end-of-life quality metrics, and encounter-level quality indicators were similar across care delivery methods []. Another retrospective chart review suggested that PPC health technology, including telemedicine consultation, paralleled face-to-face consultation in terms of documented consultation components []. In an online survey, around 67% of children in need of PPC and their parents reported that they were willing to use health technology apps []. However, families and HCPs had concerns about health technology, with too many functions being confusing and potentially leading to technological overload []. HCPs may perceive health technology as useful for enhancing communication and maintaining relationships and as a time-efficient approach to ensuring that all relevant parties are updated and included in health-related discussions []. Furthermore, HCPs highlight the potential of one shared digital platform that can store and exchange pertinent health care information to enable HCPs to deliver timely and appropriate home-based PPC [].

Several previous reviews have examined the use of health technology in home-based palliative care for adult patients [-]. One examined the use of home-based health technology for PPC but did not limit the included studies to children aged 0-18 years [].

A previous scoping review explored the existing literature on the use of health technology for home-based PPC for children aged 0-21 years. The results suggest that health technology is acceptable for both families and HCPs []. A recent mixed methods review identified and reviewed the use of health technology for communication and to support home-based PPC []. The review found that health technology should be easy to use and effective in enhancing support and communication. However, this review did not systematically map the characteristics of health technologies and infrastructures for supporting communication in home-based PPC.

Health technology is frequently used for home-based PPC. PPC is provided throughout children’s lives [,,], while adult palliative care is provided during a more limited period of the illness trajectory. Children also have different requirements when using a digital tool than adults. Consequently, evidence from adult home-based palliative care is not immediately transferable to the PPC context. Furthermore, no previous scoping review has mapped existing studies on health and communication technologies and infrastructures for supporting children in home-based PPC and their families. Such a review could provide important knowledge about existing technologies and infrastructures to help HCPs, care managers, and researchers implement health technology for home-based PPC. Facilitating the use of existing technologies rather than developing new technologies to support communication between families and HCPs would conserve resources and reduce costs. Consequently, in this scoping review, we aimed to systematically map the literature on health technologies and infrastructures for supporting communication in home-based PPC.

Methods

Study Design

We based this scoping review on the methodological framework of Arksey and O’Malley [] and current methodological guidance [,]. Arksey and O’Malley’s framework consists of the following stages: identifying the research questions; identifying relevant studies; selecting studies; charting the data; and collating, summarizing, and reporting the results. Scoping reviews address broader topics and less specific research questions than systematic reviews and can include studies with different research designs and methods in addition to gray literature []. In line with the methodological guidance [], we did not appraise the methodological quality of the included publications []. We reported the review according to the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) checklist [] (). Deviations from the published protocol [] are reported in .

Identifying the Research Questions

We formulated the following research questions: (1) What is known about existing health technologies and infrastructures for supporting communication in home-based PPC? (2) How can existing knowledge about health technologies and infrastructures inform future health technology development for home-based PPC?

Identifying Relevant Studies Through Eligibility Criteria

The eligibility criteria are described in using the population (P), concept (C), and context (C) framework [], including the period, type of literature, and language.

We included studies regardless of study design and methods and gray literature to identify a broad range of relevant publications. We limited the literature to publications in Danish, English, Norwegian, or Swedish (the languages understood by our research team). We chose the period for the searches (2018-2025) to identify up-to-date, relevant health technologies and infrastructures that can inform future research, the development of health technology and services, education, and clinical practice.

Information Sources

We performed a comprehensive search on November 27, 2023, of the ASSIA, CINAHL, Embase, MEDLINE, PsycINFO, and Web of Science databases to identify relevant literature. The database search was updated on August 28, 2025. The updated search comprised publications within 2023-2025, due to technical settings in the databases, only allowing to limit the search to whole years. Thus, the updated search will contain duplicates from the initial search, and the updated search is consequently reported as one search rather than specified to each database.

The search strategy was built in MEDLINE by 2 academic librarians (Elisabeth Karlsen and Ingjerd L Ødemark) with expertise in systematic searches for medical research databases in collaboration with the research team members SAS, EB, and HH. The search strategy was piloted by SAS and EB. Then, the search strategy was peer reviewed according to the Peer Review of Electronic Search Strategies guidelines [] by a third librarian (Camilla Thorvik). The final search strategy was adopted for the remaining databases. The search strategy covered three elements: (1) palliative care, (2) children, and (3) health technology (). We manually searched the reference lists of included studies to perform forward citation tracking using Google Scholar, and we also manually searched the Journal of Medical Internet Research and the Journal of Telemedicine and Telecare.

Study Selection

We transferred the publications identified from the database searches to EndNote (Clarivate) to remove duplicates and then transferred them to Covidence (Veritas Health Innovation). Covidence is a systematic review web tool that ensures that the study selection process is blinded and that 2 researchers independently assess all publications. In total, all authors screened the publications in 2 steps. We screened titles and abstracts, uploaded full-text publications to Covidence, and assessed them against the eligibility criteria. In both steps, conflicts among the authors were resolved by SAS or HH.

Charting the Data

We developed a standardized data charting form using Microsoft Word and included the following data items: author, year, country, type of literature, aim of study, sample, research design (when applicable), results, aim of health technology, development of health technology, users of health technology, health technology, follow-up service, mode of delivery, and infrastructure. SAS and HH piloted the data charting form using 4 publications. Based on the pilot and discussions within the research team, we collapsed some of the data items and restructured the data charting form to facilitate an overview of the extracted information. SAS and HH extracted data from the included publications, while AW, KR, and WC checked the data accuracy against the publications.

Collating, Summarizing, and Reporting the Results

The first (SAS) and last authors (HH) summarized and organized the data according to the standardized data charting form using a quantitative descriptive approach []. Data in each column of the data charting form were grouped based on similarities and differences across the included publications. For instance, studies with comparable aims were grouped based on similarities, the different groups were categorized, and then, the number of studies in each group was counted and summarized, and percentages were calculated. Studies reporting on the use of comparable health technology such as monitoring apps or reporting on the same type of infrastructure were grouped together. Furthermore, for instance, the different users of health technology (ie, children, families, HCPs, or others) and the modes of delivery (ie, asynchronous, synchronous, and both delivery modes) were counted and summarized across the publications, and then, percentages were calculated. The coauthors provided feedback and agreed on the summarization and organization of the data.

Results

Overview

Through database searches, a total of 16,209 records were identified. After we deleted duplicates, we screened the titles and abstracts of 9238 records. We then assessed the full texts of 289 publications and included 39 publications. Two of these publications were identified in the updated database search. The manual searches yielded 2 eligible publications. The final sample consisted of 41 publications ().

‎

Health Technology and Infrastructure

The characteristics of the health technologies and infrastructures reported in the included publications are described in [,-].

The Aim of Health Technology

The publications described various aims of the health technology used for home-based PPC. In 34.1% (14/41) of the publications, the aims of the health technologies were to improve symptom management and reduce treatment burdens [-]. In 29.3% (12/41) of the publications, the aim of the health technologies was to support palliative care at home [,-]; and in 12.2% (5/41) of the publications, the health technologies were designed to deliver psychosocial care and support psychosocial needs [-]. Furthermore, in 12.2% (5/41) of the publications, the aim of the health technologies was to support children and caregivers or parents [-]; in 9.8% (4/41), to improve clinical outcomes [-]; and in 2.4% (1/41), to improve communication and decision-making [].

Development of Health Technology

In 29.3% (12/41) of the publications, the researchers used user-centered and phased-design approaches to develop health technologies for PPC [,,,,,,,-,,]. Users such as children, adolescents, HCPs, and parents []; parents and professionals [,]; or parents [,] participated in the development processes. For instance, in one study, parents provided feedback at all stages of the intervention design and initial testing [], while in another, adolescents with cancer provided feedback at all stages of app development and evaluation []. The health technology development processes included multiple phases; for instance, a needs assessment or analysis was conducted by interviewing children, caregivers, and HCPs or conducting a literature review [,,,,]. The prototypes were refined and improved through usability testing (ie, think-aloud testing, beta testing by end users, and interviews with children and caregivers) [,,,,,-,].

In 4.9% (2/41) of the publications, the health technologies for home-based PPC were developed by an external web design company, while the educational information was provided by HCPs and a representative of a pain service center [,]. In 4.9% (2/41) of the publications, the health technologies or follow-up services were developed by HCPs or other professionals [,]. For instance, senior leadership (including clinical leadership), volunteer services leadership, project managers, and people with patient management system expertise were responsible for transitions to virtual hospices and the activities supporting such transitions. Furthermore, in one publication (1/41, 2.4%), the development of health technology was based on cognitive behavioral therapy [], while in another publication (1/41, 2.4%), the development was based on an unreported theory and the experiences of children, families, and the research team []. Finally, in 3 publications (3/41, 7.3%), health technology for PPC was developed based on modifying a symptom self-monitoring system [] or existing technology, such as a computer health evaluation system or EPIC [,]. However, in 46.3% (19/41) of the publications, the development of health technology and the inclusion of users in the development were not reported [,-,,,-,-,,,-,,].

Users of Health Technology and Modes of Delivery

In 46.3% (19/41) of the publications, children, families, HCPs, and other professionals used health technology [,,,,,,,,-,,,-,,,]; in 17.1% (7/41) of the publications, children and HCPs used health technology [,-,,,]; and in 36.5% (15/41) of the publications, families and HCPs used such technology [,,-,-,,-].

The most frequent mode of delivery underpinning health technology for supporting communication in home-based PPC was a combined asynchronous and synchronous mode (19/41, 46.3%) [,-,-,,,,,,,,,,,] followed by asynchronous (12/41, 29.3%) [,,,-,,-,] and synchronous (9/41, 22%) [,,-,,,] modes.

Health Technologies and Follow-Up Services

The included publications described the diverse use of health technologies for communication between children or parents and HCPs and other professionals in home-based PPC.

The most frequent health technologies for communication regarding home-based PPC described in the publications (15/41, 36.6%) were symptom monitoring apps. In these publications, it was reported how children and parents used these apps to both assess and communicate children’s symptoms using child-adapted electronic patient-reported outcome measures or objective outcomes reported by the children or their parents [,,-,-,] or how children self-reported pain or other symptoms using electronic diaries [] or through gamification [,,,,]. In some of these apps, if the reported symptoms were above predefined thresholds, HCPs received alerts and acted accordingly by contacting parents or adolescents to solve the problem [,,-,-,,]. Gamification was, for example, introduced to enable adolescents with cancer aged 12-18 years to act as law-enforcement officers or superheroes, scoring pain twice daily. If the adolescents reported pain, they received real-time pain assessments from the app and had to perform new pain assessments within 1 hour. However, if pain scores were above a certain level, nurses were alerted and contacted both the adolescents and medical teams to discuss and initiate interventions [,].

In several publications (8/41, 19.5%), video technology facilitated communication during videoconferences and telemedicine visits with children, families, and HCPs as well as provided remote outpatient clinics and music therapy [,,,-,,]. During videoconferences, nurses participated in person from the children’s homes, while PPC physicians participated remotely from hospitals [,,,]. Nurses communicated with families about what to discuss with remote physicians, conducted physical examinations, and assessed the children to support physicians’ remote observations [].

In a few publications (3/41, 7.3%), communication between parents and HCPs was facilitated by health monitoring and video technology. Children’s health was continuously remotely monitored, or parents provided data regarding the children’s health by entering the data. In addition, follow-ups consisted of video check-ups or weekly video visits with nurses or home-based HCPs [,,]. Furthermore, in one publication, hospital HCPs could also send secure messages to family members and home-based HCPs []. In another publication, video technology was included in a web program for children with cancer aged 9-18 years and their families. The children received web-based training, coaching interviews, and counseling via video mobile calls, mobile messages, and children’s stories; progressive muscle relaxation and breathing exercises; and visualization interventions. The parents were offered video interviews with the coaches []. In one publication (1/41), children and other family members participated in an online chat group consisting of 6-8 members using a chat box. These sessions were led by a psychologist and a social worker [].

In other publications (6/41, 14.6%), communication between parents and HCPs in home-based PC was facilitated using web-based technology [,-,,]. Parents received interventions for psychosocial care and support through web programs, including modules that facilitated interactive self-directed sessions (ie, using a mix of video content and skills practice) [-] or interactive activities, such as videos and fotonovellas []. Parents received follow-up from telehealth guides, who had access to all the data entered by the parents. The publications did not report how such telehealth sessions were delivered [-]. In another publication (1/41, 2.4%), a counselor tracked the parents’ progress and provided follow-up if necessary [].

In a few publications (3/41, 7.3%), electronic health record (EHR)–based systems facilitated communication regarding home-based PPC [,,]. In one publication (1/41, 2.4%), the EHR system was used for the self-monitoring of symptoms, and children or parents assessed and reported symptoms. When symptoms exceeded a certain threshold, an email alert was sent to HCPs to initiate calls if necessary []. For instance, in another publication (1/41, 2.4%), families had access to portions of their children’s EHRs to view recorded information, schedule appointments, refill prescriptions, and ask HCPs questions []. Finally, in the third publication (1/41, 2.4%), families monitored and uploaded data and participated in video consultations with HCPs using EHR software [].

Infrastructure

Around one-third of the publications accounted for health technology infrastructures, such as internet and Wi-Fi (12/41, 29.3%) [,,,,,,,,,,,], access to mobile data (2/41, 4.9%) [,], and an app that could be used when the internet was unavailable or inadequate (1/41, 2.4%) []. In addition, hotspots were used to reduce Wi-Fi barriers (2/41, 4.9%) [,].

Several types of devices, such as computers or laptops (9/41, 22%) [,,,,,,,,], tablets (9/41, 22%) [,,,,,,,], or smartphones (14/41, 34.1%) [,-,,,,,,-,], were used to access apps or web programs. A few publications (4/41, 9.8%) reported that parents could borrow smartphones or tablets for projects [,,,]. Publications (18/41, 43.9%) reported 14 different mobile apps [,,,,,,-,,,,,,,,] and 1 web app (1/41, 2.4%) []. One publication (1/41, 2.4%) reported that the app could be downloaded from Apple and Google Play Stores, while another (1/41, 2.4%) reported that there were 2 different versions of the app for children (based on the age of the children) and a family version [].

Health technology infrastructures also included 12 different types of videoconferencing platforms, such as FaceTime, Zoom, Microsoft Teams, Near Me, and Attend Anywhere (9/41, 22%) [,-,,,-]. Web cameras and headsets [] or internet protocol cameras with pan-tilt-zoom [] were used. Furthermore, in one publication (1/41, 2.4%), a chat box was used to facilitate written communication []. Some publications (3/41, 7.3%) reported the use of website infrastructure, such as Bespoke and MyQuality [,,], web-based patient portals (1/41, 2.4%) [], or web programs (2/41, 4.9%) [,]. Other publications (4/41, 9.8%) reported the use of EHR systems such as EPIC, My Chart, and Symon-SAYS [,,,].

In total, 3 publications (3/41, 7.3%) reported 3 different systems for monitoring children’s health conditions, including the Cloud DX Connected Health System (Google Inc) and Medlinecare 2.1 (Medical Online Technology SL), which monitor children’s conditions in real time at home from pediatric intensive care units. Electronic monitoring devices for such monitoring could include a pulse oximeter, scale, or tele-auscultation [,,].

Infrastructure-related aspects mentioned in the publications (4/41, 9.8%) related to the content of technology, such as web-based resources, including video content that appealed to children of different ages and parents, hands-on web-based activities, graphic publications, worksheet tools, and fotonovellas [,,,,].

The reported infrastructures also facilitated data security and privacy. Publications reported the use of secure apps, platforms, portals, or servers (7/41, 17.1%) [,,,,,,], the storage of app data on secure clouds (1/41, 2.4%) [], and the use of 2-factor authentication (2/41, 4.9%) [,]. In addition, in one publication, data entered into a website were controlled by patients or caregivers who could grant access to HCPs [], and in another publication (1/41 2.4%), data were not linked to the children’s EHRs []. In total, 3 (7.3%) publications did not provide information regarding infrastructure [,,].

Description of the Included Literature

The final sample consisted of 41 publications: 20 empirical papers, 6 protocol papers, 7 abstracts, 3 brief publications, 2 review papers, and 3 case publications. The characteristics of the included publications are described in [,-].

Empirical Papers

The empirical papers reported on studies conducted in the United States (9/20, 45%), Canada (2/20, 10%), Iran (2/20, 10%), the Netherlands (2/20, 10%), Austria (2/20, 10%), China (1/20, 5%), Indonesia (1/20, 5%), and Spain (1/20, 5%). The sample sizes reported in the empirical papers ranged from 12 to 621 participants.

The empirical papers included children (7/20, 35%) [,,,,-]; children and families (3/20, 15%) [,,]; children, families, HCPs, and other professionals (3/20, 15%) [,,]; children and HCPs (1/20, 5%) []; families (5/20, 25%) [,,,,]; and families and HCPs (1/20, 5%) [].

In 70% (14/20) of the empirical papers, the children had been diagnosed with cancer, or the families had children with cancer. In total, 13 of 20 (65%) empirical studies were based on quantitative methods [,,,,,,,,,,,], 5 of 20 (25%) on mixed or methods [,,,,], and 3 of 20 (15%) on qualitative methods [,,]. A total of 12 of 20 (60%) empirical studies assessed the feasibility, usability, usefulness, acceptability, or benefits of health technologies [,,,,,,,,,,,], while 4 of 20 (20%) aimed to develop health technologies for PPC [,,,].

Protocol Papers

The protocol papers described studies planned in the United States (3/6, 50%), Australia (1/6, 17%), Canada (1/6, 17%), and Turkey (1/6, 17%). These papers aimed to include children (3/6, 50%), children and families (1/6, 17%), children and HCPs (1/6, 17%), or families only (1/6, 17%). Most of these studies (5/6, 83%) targeted children or families of children with cancer. In total, 5 of 6 (83%) protocol papers described plans for randomized controlled trial designs [,,,,], and 1 of 6 (17%) described a mixed methods approach [].

Review Papers

The 2 review papers were conducted in Norway (1/2, 50%) and the United States (1/2, 50%). One paper was a convergent systematic mixed methods review that covered 7 empirical papers [], while the other used no systematic search and study selection method and included 112 references [].

Brief Publications

The 3 brief publications were from Austria (1/3, 33%), the United Kingdom (1/3, 33%), and the United States (1/3, 33%). These papers included children (1/3, 33%) [], nurses (1/3, 33%) [], and empirical studies (1/3, 33%) []. One paper included 152 children with cancer [], another included 15 nurses [], and the third included 3 empirical studies (prospective longitudinal studies) []. The brief report papers used retrospective cost analysis [], qualitative design (1/3, 33%) [], and a systematic review and narrative synthesis (1/3, 33%) [].

Case Publications

The 3 case publications were from Australia (1/3, 33%), Austria (1/3, 33%), and the United Kingdom (1/3, 33%). One case report included a pediatric hospice provider (1/3, 33%) [], another included an anecdotal case about a 10-year-old child with cancer (1/3, 33%) [], and the third included 3 children (1/3, 33%) [].

Conference Abstracts

The 7 identified conference abstracts were from the United States (3/7, 43%), Canada (1/7, 14%), Colombia (1/7, 14%), India (1/7, 14%), and the Netherlands (1/7, 14%). The abstracts included samples of children (3/7, 43%); children, families, and HCPs (2/7, 29%); families (1/7, 14%); and families and HCPs (1/7, 14%). In 50% (3/6) of the abstracts, the samples comprised children with cancer or family members of children with cancer. In total, 1 abstract referred to a pilot test [], 1 to a randomized controlled trial [], 1 to a cross-sectional study [], and 1 to a mixed methods study []. A total of 2 abstracts did not report methods [,], while 1 reported no methods [].

Discussion

Principal Findings

The aim of this scoping review was to systematically map the literature on health technologies and infrastructures for supporting communication in home-based PPC.

We identified and summarized numerous technologies, features, and their associated infrastructures. Overall, in a limited number of publications, the users (ie, children and caregivers) participated in the technology development process for home-based PPC, and children with cancer and their caregivers were the most frequently reported users. The most frequent delivery mode for such technology was via combined asynchronous and synchronous modes. Apps for symptom monitoring were the most frequent health technology apps for communication regarding home-based PPC. However, details of health technology infrastructures for home-based PPC were lacking or insufficiently accounted for in the publications.

Our review revealed that only 29.3% of the publications included users, such as children, caregivers, and HCPs, in the development of health technology and follow-up services. Furthermore, around 46% of the publications provided no information about the development processes or the participation of users. Consequently, we may assume that users were not included in the development in these cases. This omission was unsurprising, as another scoping review claimed that children were rarely included in research before and after interventions []. However, users may have been included in the development process, but this information may have been omitted from the papers due to the word limitation, or the researcher may be unsure what to report regarding the inclusion of users. It is imperative for users to participate in developing and tailoring health technology to align more closely with patient needs [] and to avoid posing additional strain and burden on these families causing harm. Furthermore, adults (ie, caregivers and HCPs) may not fully understand what children experience or understand and what their needs might be [,]. Therefore, including children in the development of health technology is crucial for designing effective and useful communication systems. Services for children in need of PPC must be tailored to their ages, developmental capacities, and preferences []. Future studies should strive to include children in the development of health technology and follow-up services. However, such inclusion could be challenging due to children’s health conditions. Developing personas based on, for instance, interview data about the needs of children in PPC may be one approach to include children’s voices in the development process. Personas are concrete, specific, and fictitious representations of end users and represent end users with common behavioral features that may facilitate designers’ ability to develop usable and useful designs (ie, of health technology) [] and engage users in expressing their needs []. Furthermore, future studies should develop guidelines for reporting user participation, especially when children are included in the development of health technology. This could enhance the transparency and the reliability of such development.

We found that the most frequently reported mode of delivery of health technology for communication combined asynchronous and synchronous modes. This could enable children or caregivers to report symptoms and needs at home, while HCPs are remotely available for communication, support, and interventions when needed. This approach may enhance caregivers’ perceptions of normalcy, their ability to maintain a normal family life, and their feelings of being supported at home [,]. Furthermore, caregivers may need easily accessible long-term support from HCPs to manage difficult situations in the future, especially for patients discharged from the hospital to home-based care []. Bergstraesser [] emphasized the importance of care delivery that is flexible, individualized, and considers the individual needs of children and their caregivers. Consequently, future studies should be aware that combining asynchronous and synchronous modes of delivery may facilitate children’s and caregivers’ access to and support from HCPs.

In around 17% (7/41) of the included publications, children used health technology autonomously, while in around 46% (19/41) of the publications, children used technology together with their caregivers to communicate with HCPs. The Convention on the Rights of the Child advocates for promoting children’s interests and views []. Health technology could facilitate children’s ability to express their needs to both their caregivers and HCPs. Children, especially adolescents, may appreciate direct communication with HCPs rather than communicating through their parents [], and similarly, HCPs value the opportunity to communicate directly with children []. In most of the included publications reporting on children actively participating in their care using health technology, the children had cancer diagnoses. However, children with diagnoses other than cancer may have other PPC needs, and some may have difficulty expressing themselves verbally and may communicate using eye movements [,]. Furthermore, children with diagnoses other than cancer may receive PPC from multiple sites, and their caregivers may lack a support system and feel isolated []. Health technology could mitigate the logistical issues associated with in-person consultations for children with complex medical needs, prevent interruptions to the children’s routines or medical care, and ease the complications of moving children who are medically vulnerable []. Future studies should develop or tailor health technology for children with primary diagnoses other than cancer and their caregivers to align more closely with their needs and facilitate communication with HCPs in the broader context of home-based PPC.

We found that the most frequently used health technology apps for communication in home-based PPC were symptom-monitoring apps. This attention to symptom monitoring is not surprising, as children in PPC, regardless of their diagnoses, often experience burdensome symptoms during their illness trajectories []. The aim of PPC is to prevent and alleviate burdensome symptoms and improve quality of life [], and symptom assessment is a prerequisite for optimal symptom management. Apps that allow children or caregivers to report children’s symptoms to HCPs in real time can facilitate and improve HCPs’ understanding of children’s conditions []. In several of the included publications, children used apps including patient-reported outcomes to communicate their symptoms to HCPs. Children’s voices are crucial, since self-reporting of symptoms is the gold standard for assessing symptoms, given that caregivers and HCPs often underreport the number and severity of symptoms children experience []. Patient-reported outcome data may improve care delivery by shaping children’s and HCPs’ expectations, facilitating communication about important issues, and enhancing shared decision-making, which might facilitate interventions to address children’s specific needs []. HCPs need to tailor care and symptom management to children according to their cognitive, emotional, social, and physical stages of development []. The use of existing symptom monitoring apps rather than developing new ones may conserve resources and enhance sustainability, and may be transferable to children with complex needs such as diabetes. However, as PPC includes a heterogeneous group of children with diverse and complex needs as well as various abilities to use such apps, these apps need to be tailored to both the conditions, the needs of the individual child, and the services there are to function within. Notably, only a few of the publications used gamification to allow children to report their symptoms. This absence is not surprising since gamification has been applied to a limited extent in PPC []. Gamification may support children’s creativity and provide them with choices; children may enjoy the rewards, incentives, and personalized aspects of such apps, which may also ease symptom reporting and help in specifying symptom locations []. However, a recent scoping review on gamification in mobile apps for children with disabilities demonstrated potential benefits across different populations but highlighted mixed results due to gamification’s impact on the health, health behavior outcomes, and health development of children with disabilities []. Future studies should investigate whether and how gamification could be used in home-based PPC to facilitate communication between children, caregivers, and HCPs. Studies should also investigate the possible side effects of gamification.

Our findings suggest that the internet, Wi-Fi, and mobile data are common infrastructures needed to use health technologies for home-based PPC. Even though such infrastructures were only reported in around 36% of the publications, we assumed that they were prerequisites for the technologies reported in all the publications. Information about infrastructure is essential for policymakers, health care managers, and HCPs who want to implement health technology in home-based PPC by providing information about what is needed to secure the implementation of such services and to assess resource use and cost as well as the need for training for HCPs. Dependence on access to the internet creates a new vulnerability for communication in home-based PPC and may impose an additional burden on children and parents as well as HCPs. A scoping review found that unreliable technology and connectivity issues may undermine HCPs’ confidence in using health technology, and that HCPs may feel professionally and personally responsible if health technology solutions fail []. Only a few publications reported measures to mitigate such risk, such as an app that could be used when the internet did not function properly [] and hotspots to reduce Wi-Fi barriers [,]. Mobile devices (ie, smartphones, tablets, and laptops) could also create challenges for caregivers who cannot afford such devices. The costs involved could increase health inequity and the digital divide. For instance, purchasing technology or an expensive internet plan may be a heavy financial burden that can limit technology access for families with several children. One potential solution for enhancing technology access for families in home-based PPC could be that hospitals or home care services lend out devices such as smartphones or tablets to families. Furthermore, few technology resources and low technological literacy may hinder people’s ability to engage in necessary health care activities, such as video consultations [].

The included publications mainly accounted for the type, feature, and content of the health technology and follow-up from HCPs, while the infrastructure needed to use health technology was insufficiently reported or lacking. Furthermore, even though privacy and data security are prerequisites for using health technology in home-based PPC, only a few publications have addressed these issues. Privacy and confidentiality may pose important legal and ethical challenges for the use of health technology, especially during video consultations. Furthermore, HCPs using health technology in home-based palliative care have access to large portions of patients’ daily life data, including a great deal of sensitive information. These sensitive data must be protected against unauthorized access and misuse []. An overview of the infrastructure may be essential to tailor or implement existing health technology in home-based PPC to save costs and resources and enhance sustainability. Consequently, future studies should develop a checklist for reporting health technology infrastructure and health economic evaluations.

Strengths and Limitations

A strength of our review was that we registered the review protocol a priori and used an acknowledged methodological framework to guide our review. We developed the search strategy in collaboration with experienced research librarians, and independent pairs of researchers conducted the study selection and data extraction. The inclusion of studies was limited to 2018-2025, which enabled us to identify and map up-to-date, relevant health technologies for home-based PPC. However, relevant health technologies may have been reported in studies published before 2018, which we were not able to identify. Another strength was that we searched for and included diverse literature to enhance the mapping of the existing technology for home-based PPC. However, the conference abstracts provided only limited descriptions of health technologies and infrastructures. A limitation is that we may not have identified all the relevant search terms for PPC and health technology. Our inclusion criteria restricted the review to only publications in the English and Scandinavian languages. We did not search specific databases for gray literature, but the type of literature included in our review is indexed in the chosen databases. Consequently, there may be publications that we did not identify. Furthermore, our findings may have some transferability to children with complex care needs, but it is different for children to live with a life-limiting or life-threatening condition than a chronic illness such as diabetes. However, regarding transferability, HCPs and researchers must assess whether our findings are relevant for their context.

Conclusions

Based on the included publications, children with cancer and their families are the primary users of health technology to communicate with HCPs in home-based PPC, although there is limited use among children with diagnoses other than cancer and their families. Combined asynchronous and synchronous modes are the most frequent modes of health technology delivery. Furthermore, children and their families often communicate with HCPs using symptom monitoring apps. The reporting of health technology infrastructures for home-based PPC is lacking or insufficiently accounted for.

Future studies should strive to include the voices of children, especially children with diagnoses other than cancer, to align health technology more closely with their needs. Studies should explore and evaluate whether gamification is feasible for children who require PPC and potentially develop such health technology for home-based PPC. Reporting guidelines for the inclusion of users in the development of health technology, especially children, as well as health technology infrastructure would be beneficial for supporting clinicians and researchers in gaining an overview of the infrastructure needed to implement health technology and follow-up services. This may conserve resources, reduce costs, and prevent research waste.