Category: 3. Business

With multiple chemotherapy regimens approved for the frontline treatment of patients with metastatic pancreatic cancer, patient factors such as performance status and the presence of certain comorbidities can influence the selection of an appropriate regimen for specific patients, according to Shubham Pant, MD, MBBS.

Frontline Chemotherapy in Metastatic Pancreatic Cancer

• Frontline chemotherapy options in metastatic pancreatic cancer comprised NALIRIFOX, FOLFIRINOX, and gemcitabine plus nab-paclitaxel.

• Chemotherapy selection in the frontline setting can be based on patient performance status and other underlying comorbidities.

Current frontline options include FOLFIRINOX (fluorouracil, oxaliplatin, and irinotecan), gemcitabine plus nab-paclitaxel (Abraxane), and NALIRIFOX (irinotecan liposome [Onivyde], oxaliplatin, 5-fluorouracil, and leucovorin). NALIRIFOX was the regimen most recently added to the frontline armamentarium following its FDA approval in February 20-24, based on data from the phase 3 NAPOLI 3 study.¹

Findings from the NAPOLI 3 showed that patients treated with NALIRIFOX (n = 383) experienced a median overall survival (OS) of 11.1 months (95% CI, 10.0-12.1) compared with 9.2 months (95% CI, 8.3-10.6) for those given gemcitabine plus nab-paclitaxel (n = 387; HR, 0.83; 95% CI, 0.70-0.99; P = .036).²

At the 2025 ASCO Annual Meeting, findings from a post hoc analysis of NAPOLI 3 showed that 12.5% of North American patients treated with NALIRIFOX during the study (n = 120) experienced an OS of at least 18 months.³ In this analysis of long-term survivors, investigators showed that most patients needed dose reductions of liposomal irinotecan (66.7%) and dose delays of liposomal irinotecan (86.7%), along with dose delays (80%) and dose reductions (80%) of oxaliplatin. Investigators concluded that these reductions and/or delays allowed for prolonged exposure to treatment and helped this long-term survivor group achieve a median OS of 19.5 months.

In an interview with OncLive^®, Pant outlined the key factors he examines when selecting a frontline chemotherapy regimen for a patient with metastatic pancreatic cancer, explained how NALIRIFOX fits into the current treatment paradigm, and detailed the possibility of incorporating targeted therapy into the frontline treatment setting.

Pant is a professor in Department of Gastrointestinal (GI) Medical Oncology of the Division of Cancer Medicine, director of Clinical Research, and a professor in the Department of Investigational Cancer Therapeutics at The University of Texas MD Anderson Cancer Center in Houston.

OncLive: What are some factors driving first-line chemotherapy selection in metastatic pancreatic cancer?

Pant: The biggest thing is the performance status of the patient [and] if they have any comorbidities. [For example, treatment decisions can be affected] if they have a neuropathy from diabetes, or, overall, if they have any other core issues, like nausea, vomiting, or other comorbidities leading into [treatment]. Those are the two big [factors]. I [consider] the ECG, the performance status, and any comorbidities at the same time in a patient.

How has NALIRIFOX been integrated into the frontline treatment setting for metastatic pancreatic cancer since its FDA approval in February 2024? Has there any been any challenges adopting that regimen alongside FOLFIRINOX and gemcitabine plus nab-paclitaxel?

NALIRIFOX was compared [with] gemcitabine and nab-paclitaxel [in the NAPOLI 3 trial] and was found to be a superior regimen [in terms of OS (HR, 0.84; 95% CI, 0.71-0.99; P = .0403) and progression-free survival (HR, 0.70; 95% CI, 0.59-0.85; P = .0001)]. And interestingly, NALIRIFOX has a lower chance of [inducing] neuropathy because of a lower dose of oxaliplatin that was used in [NAPOLI 3].

However, we do have to watch out for diarrhea in our patients [treated with NALIRIFOX], which can be slightly increased. If a patient is already having diarrhea issues with gut intolerance, then we would tend to use another alternative regimen. Otherwise, I think [NALIRIFOX] a very appropriate regimen for patients in the frontline setting.

As the research continues to progress, how do you see targeted therapies or other agents impacting the first-line treatment paradigm in metastatic pancreatic cancer?

That is a great question because we have a lot of targeted agents that are coming into the field. The ones that are furthest along are the pan-RAS inhibitors, [including] a drug called daraxonrasib [RMC-6236], which is [being evaluated] in the phase 3 [RASolute 302] clinical trial [NCT06625320] in the second-line setting [for patients with metastatic pancreatic ductal adenocarcinoma].

Then we have a number of KRAS G12D inhibitors; approximately 40% of [patients with] pancreatic cancer [harbor KRAS G12D mutations], and we are testing [KRAS G12D inhibitors] as single agents and in combinations of chemotherapy. All that means that there is a lot of excitement in the pancreatic cancer space, and hopefully we should get more options for our patients in the near future.

With November being Pancreatic Cancer Awareness Month, what would be your message for your colleagues regarding the push to integrate new treatment approaches in the space?

[Clinicians] should, when appropriate, conduct next-generation sequence testing. And if a patient is appropriate for clinical trials, we should try to find a clinical trial for them. That’s important. Hope is on the horizon for this disease, and hopefully, we should be able to get some newer therapeutics for our patients.

References

1. FDA approves irinotecan liposome for first-line treatment of metastatic pancreatic adenocarcinoma. FDA. February 13, 2024. Accessed November 23, 2025. https://www.fda.gov/drugs/resources-information-approved-drugs/fda-approves-irinotecan-liposome-first-line-treatment-metastatic-pancreatic-adenocarcinoma
2. Wainberg ZA, Melisi D, Macarulla T, et al. NALIRIFOX versus nab-paclitaxel and gemcitabine in treatment-naive patients with metastatic pancreatic ductal adenocarcinoma (NAPOLI 3): a randomised, open-label, phase 3 trial. Lancet. 2023;402(10409):1272-1281. doi:10.1016/S0140-6736(23)01366-1
3. NAPOLI 3 phase 3 study of NALIRIFOX in metastatic pancreatic ductal adenocarcinoma: characteristics of the long-term survivors. J Clin Oncol. 2025;43(suppl 17):LBA4175. doi:10.1200/JCO.2025.43.17_suppl.LBA4175

Welcome to Tech In Depth, our daily newsletter about the business of tech from Bloomberg’s journalists around the world. Today, Austin Carr looks at Google’s decision to outsource interface design to its ever-evolving Gemini tools.

Yesteryear’s best: The Trump administration has talked internally about letting Nvidia sell its H200 AI chips in China. The export restrictions on powerful AI chips have been among the most contentious issues of the US-China trade dispute.

Amazon Leo is designed to extend reliable, high-speed internet to those beyond the reach of existing networks, including the millions of businesses, government entities, and organizations operating in places without reliable connectivity. Amazon Leo will help close critical connectivity gaps across major industries, from energy and manufacturing to media and transportation, and these announcements represent another important step for the program as it moves from the deployment phase toward commercial operations.

Speech by Christine Lagarde, President of the ECB, BratislavAI Forum on artificial intelligence and education as part of an OECD high-level event to mark the 25th anniversary of “Better Policies for Better Lives”, Bratislava

Bratislava, 24 November 2025

It’s a privilege to speak with you today about artificial intelligence.

In 1987 Robert Solow famously remarked that “you can see the computer age everywhere but in the productivity statistics.”

The same observation could be made today. We see AI advancing at remarkable speed. Yet its aggregate impact is still barely visible in the data.

Over the past year global corporate investment in AI reached USD 252 billion, and private AI firms raised a record USD 100 billion.^[1] Five leading US investors in terms of capital expenditure are now companies that focus heavily on AI. None of these companies numbered among the top ten investors a decade ago. ^[2]

Some view this surge as temporary exuberance running ahead of underlying fundamentals. But a debate framed only in terms of short-term ups and downs may miss the bigger picture.

History offers many examples of intense investment waves that – despite swings in the investment cycle – ultimately left behind transformative technologies that reshaped economies for decades.^[3]

So the key question is not whether there are cycles – that is almost certain – but how long it will take before the enduring productivity benefits become visible.

And there are reasons to believe AI could spread faster, and deliver tangible economic gains sooner, than previous technology waves.

If that is the path we are on – and I believe it may be – Europe needs to position itself accordingly. We need to remove all the obstacles that stop us from embracing this transformation. Otherwise we risk letting the wave of AI adoption pass us by and jeopardise Europe’s future.

History shows: disruptions first, benefits later

To understand what is at stake, it is useful to look at history.

Earlier general purpose technologies, such as electricity, computers or the internet, followed a recognisable trajectory. Disruption arrived early, with broad-based productivity gains only emerging slowly.^[4]

For example, it took around thirty years before the impact of electricity showed up clearly across the economy. Power grids had to be built, factories redesigned and workers reallocated from legacy tasks to new ones.

Computers, too, required long-term investments in hardware, software, skills and new business models before they translated into measurable improvements.

If Europe’s AI wave resembles the spread of electricity in the 1920s, annual productivity growth could be about 1.3 percentage points higher. But if it follows the US digital boom of the late 1990s, the boost would be closer to 0.8 points.^[5] Even that lower bound would be significant for Europe, marking a clear step up from recent trend productivity.

Could this time be different?

But AI has features that could compress this cycle and push forward even greater productivity gains. Two features – innovation and diffusion – point to a faster path.

The first is that frontier innovation may accelerate because of the recursive nature of AI.

AI systems can use their own output to enhance their performance in a continuous loop. This can lower not only the cost of producing goods and services, but also the cost of generating new ideas.^[6]

For instance, in fifty years, science resolved approximately 200,000 protein structures. AI achieved over 200 million protein structure predictions in about one year, vastly expanding the knowledge frontier.^[7]

This represents a significant change in the inputs to research and development. As the knowledge base expands almost overnight, downstream discovery can compound sooner, even before every lab or firm has fully reorganised.

By accelerating the production of ideas, AI can lift not just the level of productivity but potentially the growth rate itself.^[8] Some estimates suggest that such AI-augmented R&D could double recent US productivity growth rates to between 1.6 and 2.4% annually – faster than previous technology waves.^[9]

Second, the diffusion of AI technologies can be faster because much of the supporting infrastructure already exists.

It is true that there are bottlenecks. The current wave of investment in hyperscalers shows that compute capacity remains a constraint. Training and deploying larger models requires substantial investment in data centres and energy. In Europe we face particular challenges in this respect, given our higher energy costs and longer permitting delays.

But unlike past technologies, such as electricity or computers that required new physical networks or coding skills, AI runs on existing internet devices and communicates with users through human language.

Wide-scale use can therefore proceed even before the infrastructure build-out is complete. Many AI applications already deliver gains on existing hardware. So while a lack of computing capacity holds back the pace of model development, it does not necessarily block diffusion across the wider economy.^[10]

Moreover, the infrastructure itself is advancing quickly. While Moore’s Law forecasts a doubling in chip capacity every two years, AI model compute power has been doubling every six months – four times faster.

What Europe stands to gain

What does this mean for Europe?

The stakes could be extraordinarily high.

With the United States and China ahead of the field, Europe has already missed the opportunity to be a first mover in AI. And we still bear the costs of having been slow adopters during the last digital revolution. We cannot afford to make the same mistake again.

Yet the story is far from over. Europe can still emerge as a strong second mover if it acts decisively. Our goal should not be to out-build the leading AI models, but rather to deploy AI across the board. By focusing on rapid adoption and smart use of existing AI technologies across our wide-ranging industries, Europe can turn a late start into a competitive edge.^[11]

Our economy is highly diversified. The top ten firms in the US stock market account for roughly 40% of the market across just four sectors, whereas the top ten in the EU account for no more than 18% across almost twice as many sectors.

And European firms are already adopting generative AI on a similar scale to those in the United States. What the ECB is hearing from large European companies confirms this trend: many are investing heavily in databases, cloud solutions and AI, with providers of these services reporting double-digit growth.^[12]

But to turn these benefits into a competitive advantage, we need to connect data across sectors. Thanks to industrial-scale data spaces, companies can share operational data and create training sets for AI models that no single firm could assemble alone.^[13]

Initiatives like Manufacturing-X and Catena-X in the automotive sector foster collaboration in data sharing, while the European Health Data Space enables interoperable health records, allowing us to leverage the broad anonymised patient datasets generated by our universal healthcare systems.^[14]

But these efforts will not be enough on their own.

If our data spaces use technology stacks that are owned and governed outside Europe, we deepen – rather than reduce – our strategic dependencies. We must diversify critical parts of the AI supply chain and avoid single points of failure. In the foundational layers, such as compute capacity based on chips and data centres, we should maintain a minimum capacity.

In the application layer, Europe should leverage the power of the Single Market to enforce interoperability and open standards. This will encourage competition among large models and prevent the kind of “lock-in” that has occurred with technology platforms in the past.

Moreover, we must overcome a familiar set of old barriers that have prevented us from being first movers in the past.

If we allow our energy costs to stay high, if regulations remain fragmented, and if capital markets fail to integrate and channel long-term, risk-bearing funding at scale, AI will diffuse more slowly.

And this time, the consequences extend beyond losing the race in AI models. We would eventually face a further loss of competitiveness for many of our sectors and industries.

Conclusion

Let me conclude.

“It’ll be ten times bigger than the Industrial Revolution – and maybe ten times faster.” These words from Demis Hassabis – joint winner of the 2024 Nobel Prize in Chemistry for his AI research – capture the potential scale and speed of what may lie ahead.

So the question is no longer whether this new frontier will arrive, but how soon – and the pace of progress in recent years suggests it is likely to be sooner than our institutions and regulations are prepared for.

That means acting now to clear the obstacles that would slow AI diffusion and so delay prosperity for all Europeans in the decades ahead.

Intercontinental Exchange (NYSE: ICE) and Benchmark Mineral Intelligence (BMI) today – Monday 24 November – announce the launch of new lithium and cobalt futures contracts settled against Benchmark’s trade‑verified price assessments.

Their listing on ICE Futures  Europe represents another milestone in the maturation of the battery metals market – connecting dependable physical market benchmarks to globally regulated trading venues.

Closing the basis risk gap

For many commercial participants in the battery metal supply chain, aligning physical market pricing with financial market instruments has been challenging.

Variations between different reference prices have created measurable basis risk and made it difficult for some treasuries to achieve hedge accounting treatment under IFRS guidelines.

The Benchmark (BMI) futures contracts on ICE, settled against Benchmark’s IOSCO‑assured, transaction‑based assessments, now offer a route to closer alignment between physical exposures and financial hedges.

This development improves pricing transparency and provides corporate and financial users with the tools to manage lithium and cobalt price risk more effectively across both physical and derivative markets.

“These contracts expand, rather than compete with, existing lithium and cobalt derivatives by addressing an unmet hedging need for the majority of the ex‑China supply chain,” shared Daniel Fletcher-Manuel, Benchmark’s Director of Indexing & Derivatives.

“They provide a transparent, regulated pathway for manufacturers, producers, and investors to manage battery metal price exposure across the same indices that underpin billions of dollars in offtake and supply agreements” he added.

Benchmark Chief Operating Officer, Caspar Rawles, commented:

“For the first time, participants across the supply chain, from producers to consumers and financial institutions, can trade using Benchmark’s market leading, trusted price assessments, backed by years of independent data, analysis, and market specific methodologies.This is a defining step for the global energy transition.

“By bringing transparent and independently verified transaction prices for lithium and cobalt to regulated futures markets, we’re helping to build confidence, manage risk, and support the sustainable growth of supply chains powering these new energy supply chains.”

About the partnership

Intercontinental Exchange (ICE) operates some of the world’s leading exchanges and clearing houses, including ICE Futures Europe, ICE Futures U.S., and the New York Stock Exchange.

Benchmark Mineral Intelligence is the independent data provider for the lithium‑ion battery and energy transition supply chain, publishing daily trade‑verified, IOSCO‑assured price assessments used widely in global physical and financial contracts.

The BMI futures contract suite includes:

• Lithium Carbonate CIF Asia (BMI) Future

• Lithium Hydroxide CIF Asia (BMI) Future

• Spodumene Concentrate FOB Australia (BMI) Future

• Cobalt Hydroxide CIF Asia (BMI) Future

These futures contracts connect transparent price discovery with regulated market infrastructure, enabling effective hedging for the world’s battery metal supply chain.

Learn more about BMI lithium futures or BMI cobalt futures and start trading today.

The sequential intracerebroventricular (ICV) and intraventricular (IV) administration of CR7-GD2 CAR T-cell therapy was found to be better tolerated vs concurrent administration in pediatric patients with central nervous system (CNS) tumors, according to data from a phase 1 study (NCT04099797) presented at the 2025 Society of Neuro-Oncology Annual Meeting.¹

During the study, investigators at Baylor College of Medicine in Houston, Texas, evaluated 3 administration techniques for the CR7-GD2 CAR T-cell therapy: IV only; concurrent ICV and IV; and sequential ICV and IV.

Findings showed that in patients treated with IV-only administration (n = 8) at 10 million cells/m² (n = 3) or 30 million cells/m² (n = 6), no dose-limiting toxicities (DLTs) were reported, and instances of tumor inflammation–associated neurotoxicity (TIAN) were low grade, occurring in 7 patients. One patient experienced transient grade 4 cytokine release syndrome (CRS); 5 experienced grade 1 CRS. Among patients treated via IV alone who had preexisting neurological defects (n = 7), 6 achieved clinical improvement, including 2 partial responses on imaging, which 1 patient maintained for more than 2 years.

ICV/IV Administration of CAR T-Cell Therapy in Pediatric CNS Tumors

• Sequential ICV and IV administration was found to be better tolerated compared with combined ICV and IV treatment.

• Two DLTs were reported in the combined administration group vs none in patients given sequential treatment.

• In the sequential cohort, patients experienced only low-grade TIAN/CRS and had clinical stability.

In patients who received concurrent ICV/IV administration (n = 3), with doses given 1 week apart, 2 experienced DLTs secondary to grade 3 TIAN, including 1 patient with concurrent grade 3 CRS. These DLTs persisted for several weeks and required intervention with anakinra and dexamethasone. In this group, 1 patient achieved a mixed response with transient clinical improvement and stable disease burden. The remaining 2 patients had clinical and radiographic progression.

The neurotoxicity observed with concurrent administration prompted investigators to adopt a sequential strategy, with ICV administration given 4 weeks after IV treatment. In patients treated with this strategy (n = 3), treatment was well tolerated for at least 3 cycles each, with no DLTs reported; these patients experienced low-grade TIAN/CRS and clinical stability.

“While back-to-back ICV/IV dosing resulted in increased toxicity compared [with] IV-only therapy, sequential dosing was better tolerated, potentially indicative of the negative sequelae of compounded inflammation,” lead study author Jasia Mahdi, MD, and colleagues wrote in a poster presentation of the data. Mahdi is a pediatric neurologist and neuro-oncologist, and director of Neuro-Oncology for the Division of Pediatric Neurology at Texas Children’s Hospital, as well as an assistant professor of pediatrics-neurology at Baylor College of Medicine.

How was the phase 1 study conducted?

The single-center trial enrolled 2 cohorts of patients between 12 months and 22 years of age.² The first included patients with histologically confirmed, GD2-expressing or H3K27-altered, diffuse midline glioma (DMG) or high-grade glioma (HGG) that was newly diagnosed, defined as prior to radiographic progression or recurrence; patients with histologically confirmed, GD2-expressing or H3K27-altered, recurrent, refractory, or progressive DMG/HGG; and those with recurrent, refractory, or progressive high-grade CNS tumors with confirmed GD2-expression. Cohort 2 included patients with recurrent, refractory, or progressive pontine HGG with confirmed GD2-expression or H3K27-altered DMG.

All patients needed to have tumors less than 5 cm in maximum dimension, measurable disease on at least 2 dimensions per MRI, and a Karnofsky/Lansky performance status of at least 50.

The C7R-GD2 CAR T-cell therapy was administered after lymphodepleting chemotherapy in all arms and cohorts, comprising 2 days of cyclophosphamide and 3 days of fludarabine.¹ In patients who received combined dosing, the CAR T-cell therapy was given at 5 x 10⁶ cells/m² ICV, followed by 15 x 10⁶ cells/m² IV, then another IV dose at the same level. In the sequential cohort, patients received an IV dose at 10 million cells/m², followed by an ICV dosing in cycle 2 and beyond, starting at 2 million cells and escalating to 5 million cells.

In both ICV arms, patients remained for inpatient monitoring for 6 to 10 days, followed by close outpatient follow-up. Disease evaluation occurred at week 6.

The incidence of DLTs was the trial’s primary end point.² Response rate was a secondary end point.

In the combined ICV/IV arm, 1 male patient and 2 female patients had a median age of 15 years (range, 4-17).¹ Tumor locations included thalamus and midbrain (n = 1), pons (n = 1), and C1-C7/T1 (n = 1). All had H3K27-altered DMG. Patients had a median time since diagnosis before enrollment of 9.4 months, and they had a median time from the end of radiation to enrollment of 6.5 months. These patients received a median of 1 ICV infusion.

In the sequential cohort, all 3 patients were male with a median age of 16 years (range, 14-17). Tumor locations comprised the thalamus (n = 2) and the temporal lobe (n = 1). Tumor types included H3K27-altered DMG (n = 2) and H3 wild-type, IDH wild-type diffuse HGG (n = 1). Patients had a median time from diagnosis to enrollment of 7.4 months, and a median time from the end of radiation to enrollment of 2.3 months. This group received a median of 3 ICV infusions.

What were the toxicity profiles of combined and sequential ICV/IV CAR T-cell therapy administration?

In the combined ICV/IV arm, adverse effects included CRS (grade 1, n = 2 infusions; grade 3, n = 1 infusion), immune effector cell–associated neurotoxicity syndrome (ICANS; grade 0, n = 3 infusions), and TIAN (grade 1, n = 1 infusion; grade 3, n = 2 infusions). Two patients received tocilizumab (Actemra), and all 3 were given dexamethasone, which continued upon hospital discharge.

In the sequential group, toxicities included CRS (grade 0, n = 13 infusions; grade 1, n = 3 infusions), ICANS (grade 0, n = 16), and TIAN (grade 0, n = 2 infusions; grade 1, n = 14 infusions). All patients required tocilizumab, but no patients received dexamethasone.

What was reported from a trial case study?

Investigators highlighted a 16-year-old male patient with H3K27-altered thalamic and periventricular occipital lobe DMG who underwent 9 cycles of treatment in the sequential ICV/IV arm, including 1 IV infusion and 8 ICV infusions. This patient remained on treatment as of data cutoff, and he has experienced CRS and TIAN at a maximum grade of 1. MRI revealed stable disease, and the patient was also stable on a neurological exam.

References

1. Mahdi J, Stuckert A, Tat C, et al. Phase I study of intravenous and intracerebroventricular C7R-GD2.CAR T cell therapy for pediatric central nervous system (CNS) tumors. Presented at 2025 Society of Neuro-Oncology Annual Meeting; November 19-23, 2025; Honolulu, HI. Abstract CTP-07.
2. C7R-GD2.CAR T cells for patients with GD2-expressing brain tumors (GAIL-B). ClinicalTrials.gov. Updated September 4, 2025. Accessed November 23, 2025. https://clinicaltrials.gov/study/NCT04099797