Boeing said Monday that it has completed a $4.7 billion purchase of key supplier Spirit AeroSystems, which builds fuselages for the giant aerospace company’s 737 Max jetliners, including an Alaska Airlines aircraft that suffered a door-panel blowout last year.
The deal, in the works for over a year, brings Boeing’s largest provider of spare parts in-house. CEO Kelly Ortberg called it a “pivotal moment” for the company’s future.
“As we welcome our new teammates and bring our two companies together, our focus is on maintaining stability so we can continue delivering high quality airplanes, differentiated services, and advanced defense capabilities for our customers and the industry,” Ortberg said in a statement.
Boeing previously owned Wichita, Kansas-based Spirit but spun it off in 2005. Reabsorbing the company, which is not related to Spirit Airlines, reverses a longtime Boeing strategy of outsourcing major work on its passenger planes, an approach that faced mounting criticism in recent years as manufacturing problems at Spirit disrupted production and delivery of popular Boeing jetliners, including 737s and 787s.
When Boeing announced in July 2024 that it planned to reacquire Spirit, it positioned the move as a step toward improving quality and safety. Concerns about safety came to a head almost six months earlier, after the door panel flew off the Alaska Airlines plane as it traveled 16,000 feet (4,876 meters) over Oregon.
The mishap left a gaping hole in the side of the jetliner, but no one was seriously injured. Investigators with the National Transportation Safety Board later said that four bolts that help secure door panels were missing from the Alaska jet after repair work at a Boeing factory.
The finding renewed questions about Boeing’s safety culture and came as the company confronted an ongoing criminal case over two earlier fatal crashes involving its Max jetliners.
Those crashes, which happened off the coast of Indonesia and in Ethiopia less than five months apart in 2018 and 2019, killed 346 people and led to a worldwide grounding of the 737 Max for nearly two years. The Justice Department accused Boeing of deceiving regulators about a flight-control system that was later implicated in the crashes.
The criminal case was resolved just last month, when a federal judge in Texas approved the Justice Department’s request to dismiss the charge as part of a deal with Boeing. In exchange, Boeing agreed to pay or invest an additional $1.1 billion in fines, compensation for the crash victims’ families, and internal safety and quality measures.
The total value of the Spirit acquisition is around $8.3 billion, Boeing has said. Shares of Boeing rose roughly 2% in midday trading Monday.
Striking a judicious balance between the risks of ischemia and bleeding is challenging during management of patients with acute coronary syndromes (ACS) undergoing percutaneous coronary intervention (PCI) with optimal dual antiplatelet therapy (DAPT).
The intensity and duration of antiplatelet therapy needs to be personalized on the basis of patient risk profiles, including bleeding and ischemic risks.
Despite emerging evidence for abbreviated DAPT in specific situations, 12 months of DAPT would remain the default for most patients with ACS not at high bleeding risk, especially those who have undergone PCI.
The optimal management of dual antiplatelet therapy (DAPT) in patients presenting with acute coronary syndromes (ACS) undergoing percutaneous coronary intervention (PCI) remains a dynamic and evolving area. Striking a delicate balance between ischemic protection and the risk of bleeding complications is the key challenge.1 Randomized controlled trials (RCTs), including patients with ACS requiring PCI, have almost consistently demonstrated that reduced DAPT durations are not associated with increased rates of ischemic events.2 Notably, compared with standard DAPT, the patients assigned to short DAPT durations experienced much less major bleeding.2 The assessment of DAPT in RCTs has progressively involved shorter durations (1-to-3 months of DAPT) followed by P2Y12 inhibitor monotherapy, compared with standard 12-month DAPT.3 Against this background and in light of the substantial advance in stent technology and procedural optimization, it has been proposed that stopping aspirin at discharge and continuing potent P2Y12 inhibitor monotherapy may be as safe and effective as standard prolonged DAPT for patients admitted for ACS who were successfully revascularized by PCI without significant residual coronary artery disease.
The NEO-MINDSET (Percutaneous Coronary Intervention Followed by Antiplatelet Monotherapy in the Setting of Acute Coronary Syndromes) study investigated the effects of immediate postprocedural aspirin withdrawal in patients taking DAPT who underwent PCI for ACS.4 The study involved 3,400 patients within the first 4 days of hospitalization following a successful PCI, who were randomly assigned to either discontinuation of aspirin and continuation of a potent P2Y12 inhibitor monotherapy (ticagrelor or prasugrel) or to receive DAPT that included aspirin and a potent P2Y12 inhibitor for 12 months. The primary endpoint events (death from any cause, myocardial infarction [MI], stroke, or urgent revascularization) occurred in 7% of patients in the monotherapy group and 5.5% in the DAPT group (pnoninferiority = 0.11). Major or clinically relevant nonmajor bleeding occurred in 2% of patients in the monotherapy group and 4.9% of patients in the DAPT group, and stent thrombosis occurred in 0.7% and 0.2% in the matched groups. These findings indicate that immediate P2Y12 inhibitor monotherapy with withdrawal of aspirin is not as protective as DAPT for ischemic events in patients with ACS after PCI, even though it does reduce bleeding. Whereas reductions in major bleeding despite numerically increased ischemic events may be appealing in patients at high bleeding risk (HBR), this trade-off appears less favorable in patients without HBR. Only one-fifth of patients in the NEO-MINDSET study were classified as at HBR. Ongoing trials, such as LEGACY (Less Bleeding by Omitting Aspirin in Non-ST-segment Elevation Acute Coronary Syndrome Patients), will likely shed light on unaddressed questions.5
The TARGET-FIRST (Evaluation of a Modified Anti-Platelet Therapy Associated With Low-dose DES Firehawk in Acute Myocardial Infarction Patients Treated With Complete Revascularization Strategy) trial included patients who had successfully undergone PCI with advanced drug-eluting stents within 7 days of MI and had completed 1 month of DAPT without ischemic complications or major bleeding. After randomization, patients were assigned to receive either P2Y12 receptor inhibitor monotherapy or DAPT for 11 months. P2Y12 inhibitor monotherapy was noninferior to DAPT for cardiovascular and cerebrovascular outcomes, and superior in reducing clinically relevant bleeding, supporting de-escalation in carefully selected patients at low risk.6 No previous RCT has assessed early aspirin discontinuation in patients with acute MI who achieve early, complete revascularization with modern stents. These results reflect the benefits of modern stents, high procedural success, and optimal medical therapy, making early aspirin discontinuation feasible in this select population.
The optimal antiplatelet therapy is not well established for patients who have undergone complex PCI procedures and are at high risk of ischemic events. The TAILORED-CHIP (TAILored Versus COnventional AntithRombotic StratEgy IntenDed for Complex HIgh-Risk PCI) trial included 2,018 patients with high-risk anatomical or clinical characteristics undergoing complex PCI.7 They were randomly assigned to receive either standard DAPT (clopidogrel plus aspirin for 12 months) or early escalation (low-dose ticagrelor at 60 mg twice daily plus aspirin for 6 months), followed by late de-escalation (clopidogrel monotherapy for 6 months). Overall results indicated that there was no significant difference between tailored therapy and standard DAPT in terms of the incidence of major ischemic events at 12 months. However, with tailored therapy, the incidence of clinically relevant bleeding was considerably higher. This finding challenges the notion that more is better even in carefully selected patients at high ischemic risk undergoing complex PCI procedures.
The ongoing theme across all trials is to strike a judicious balance between risks of ischemia and bleeding. The trend is toward personalized antiplatelet therapy, moving away from a one-size-fits-all approach. Patient risk profiles, including bleeding and ischemic risks, are crucial for determining the intensity and duration of therapy. It is critical to use bleeding risk scores and shared decision-making to help patients and clinicians weigh potential benefits and harms of different antiplatelet regimens. Despite emerging evidence for abbreviated DAPT in specific situations, 12 months of DAPT remains the default for most patients with ACS not at HBR, especially those who have undergone PCI.
References
Byrne RA, Rossello X, Coughlan JJ, et al. 2023 ESC guidelines for the management of acute coronary syndromes. Eur Heart J. 2023;44(38):3720-3826. doi:10.1093/eurheartj/ehad191
Valgimigli M, Landi A, Angiolillo DJ, et al. Demystifying the contemporary role of 12-month dual antiplatelet therapy after acute coronary syndrome. Circulation. 2024;150(4):317-335. doi:10.1161/CIRCULATIONAHA.124.069012
Giacoppo D, Matsuda Y, Fovino LN, et al. Short dual antiplatelet therapy followed by P2Y12 inhibitor monotherapy vs. prolonged dual antiplatelet therapy after percutaneous coronary intervention with second-generation drug-eluting stents: a systematic review and meta-analysis of randomized clinical trials. Eur Heart J. 2021;42(4):308-319. doi:10.1093/eurheartj/ehaa739
Guimarães PO, Franken M, Tavares CAM, et al. Early withdrawal of aspirin after PCI in acute coronary syndromes. N Engl J Med. Published online August 31, 2025. doi:10.1056/NEJMoa2507980
van der Sangen NMR, Küçük IT, Sivanesan S, et al. Less bleeding by omitting aspirin in non-ST-segment elevation acute coronary syndrome patients: rationale and design of the LEGACY study. Am Heart J. 2023;265:114-120. doi:10.1016/j.ahj.2023.07.011
Tarantini G, Honton B, Paradies V, et al. Early discontinuation of aspirin after PCI in low-risk acute myocardial infarction. N Engl J Med. Published online August 31, 2025. doi:10.1056/NEJMoa2508808
Kang DY, Wee SB, Ahn JM, et al. Temporal modulation of antiplatelet therapy in high-risk patients undergoing complex percutaneous coronary intervention: the TAILORED-CHIP randomized clinical trial. Eur Heart J. Published online August 31, 2025. doi:10.1093/eurheartj/ehaf652
Clinical Topics:
Acute Coronary Syndromes, Invasive Cardiovascular Angiography and Intervention, Interventions and ACS, Stable Ischemic Heart Disease
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: 67th 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
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
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
Kwan N. The impact of pharmacy deserts. US Pharm. 2024;49(4):32-36.
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
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.
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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.
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.
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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
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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.
Development, benchmarking, and validation of Gcoupler computational framework.
(a) Schematic workflow depicting different modules of the Gcoupler package. Of note, Gcoupler possesses four major modules, that is, Synthesizer, Authenticator, Generator, and BioRanker. (b) AUC–ROC curves of the finally selected model for each of the indicated GPCRs. Note: Experimentally validated active ligands and decoys were used in the testing dataset. (c) Bar graphs depicting the sensitivities and specificities of the indicated GPCRs with experimentally validated active ligands and reported decoys. (d) The AUC–ROC curve indicates the model’s performance in the indicated conditions. (e) Bar graphs indicating the prediction probabilities for each experimentally validated ligand. (f) Schematic workflow illustrates the steps in measuring and comparing the structural conservation of the GPCR–Gα-protein interfaces across human GPCRs. (g) Snake plot depicting the standard human GPCR two-dimensional sequence level information. Conserved motifs of the GPCR–Gα-protein interfaces are depicted as WebLogo. Asterisks represent residues of conserved motifs present in the GPCRs–Gα-protein interfaces. Of note, the location of the motifs indicated in the exemplary GPCR snake plot is approximated. (h) Schematic workflow illustrates the steps in measuring and comparing the structural conservation of the GPCR–Gα-protein interfaces across human GPCRs. (i) Representative structures of the proteins depicting highly conserved (low root mean square deviation [RMSD]) and highly divergent (high RMSD) GPCR–Gα-protein interfaces. PDB accession numbers are indicated at the bottom. (j) Heatmap depicting the RMSD values obtained by comparing all the GPCR–Gα-protein interfaces of the available human GPCRs from the protein databank. Of note, the RMSD of the Gα–protein cavity was normalized with the RMSDs of the respective whole proteins across all pairwise comparisons. (k) Heatmap depicting the pairwise cosine similarities between the in silico synthesized ligands of the GPCR–Gα-protein interfaces of the available human GPCRs using Gcoupler. (l) Schematic diagram depicting the hypothesis that the intracellular metabolites could allosterically modulate the GPCR–Gα interaction.
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.
