Need for Speed: AACR-Industry Roundtable 2026 Examines Strategies to Accelerate Drug Development

Advances in cancer research are racing ahead, generating new insights and therapeutic opportunities at an unprecedented pace. The pace of innovation has become a sprint; however, getting new therapies to patients remains a marathon—the systems that translate discoveries into treatments have not evolved at the same speed as scientific progress.

To address this important topic and explore how changes across the drug development pathway could help close this gap, members of the American Association of Cancer Research (AACR) Sustaining Membership Program gathered at the annual AACR-Industry Roundtable.

The meeting brings together sustaining members from biotechnology and pharmaceutical companies, academic researchers, patient advocates, U.S. Food and Drug Administration (FDA) officials, and AACR leaders to identify barriers to progress and discuss opportunities for improvement in the cancer drug development space.

Chaired by Manuel Hidalgo, MD, PhD, FAACR, a professor at NYU Grossman School of Medicine, this year’s meeting examined strategies to accelerate the clinical development process at a time of rapid scientific advances and increasing demand for timely patient access to new therapies.

Calling the topic especially timely, Hidalgo stressed that efforts to accelerate development must remain guided by rigorous science, noting that “speed must not come at the expense of evidence or patient benefit.”

The program featured presentations, panel discussions, and breakout groups, facilitating an engaging and discussion-focused meeting environment.

Prioritizing Patient Voices

Accelerating drug development requires more than improving laboratory methods or clinical trial operations. A vital component is ensuring that research addresses the needs and priorities of people affected by cancer.

Patient advocate Carole Baas, PhD, became involved in advocacy after being diagnosed with breast cancer shortly after earning her doctoral degree in biomedical engineering and welcoming her second child. In her keynote address, she discussed how patients can help shape therapeutic development from its earliest stages.

“How do we better connect the patient community to research?” Baas asked.

She emphasized the importance of engaging patients early, beginning at the preclinical stage of research and continuing through clinical trial design. Meaningful engagement extends beyond representation. Patients can help researchers identify outcomes that matter most, understand the practical burdens of participation, and design studies that better reflect the experiences of people living with cancer.

Building Better Preclinical Models

Conventional cell lines and animal models do not always capture the complexity of human tumors or predict how patients will respond to treatment. During his keynote, Hidalgo highlighted how these limitations can contribute to failures later in drug development.

In addition, Tiffany Ricks, PhD, deputy division director in pharmacology and toxicology at the FDA’s Office of Oncologic Diseases in the Center for Drug Evaluation and Research, discussed the agency’s efforts over the past two decades to reduce the use of animal testing in preclinical studies. She noted recent policy efforts to expand the use of alternative research methods and reduce reliance on animal testing when scientifically appropriate.

New approach methodologies (NAM) offer ways to improve the relevance of preclinical research to human biology while reducing animal usage. Presentations from academic researchers, Benjamin Hopkins, PhD, an assistant professor of research at Weill Cornell Medical College, and David Beebe, PhD, a professor at the University of Wisconsin–Madison, illustrated how more accurate models of human cancer—such as patient-derived “mini tumor” organoids or “organ-on-a-chip” systems—could strengthen decisions throughout drug development, improving the quality and speed of a study.

Reimagining Clinical Trials

Even when researchers identify promising treatments and the patients most likely to benefit, traditional clinical trial designs can slow progress. Discussions explored how more adaptive study designs, better use of data, and new oncology endpoints could help researchers answer important questions more efficiently.

Designing More Efficient Trials

Traditional clinical trials often operate in silos. Instead of sharing resources, each trial develops its own protocol and recruits its own patients, even when evaluating treatments for the same disease. The roundtable discussed how master protocols, including platform, basket, and umbrella trials, provide a framework for evaluating multiple treatments or patient groups within a single trial structure. Examples like I-SPY 2 in breast cancer, Lung-MAP in lung cancer, and NCI-MATCH, which matches treatments based on tumor molecular alterations, demonstrate the feasibility of this approach.

During his presentation, Hidalgo noted, “Platform trials can improve efficiency, but only with rigorous governance, strong statistical design, and high-quality operations.” Conversations bounced off this idea and noted that in certain situations, a platform trial may not be the most appropriate approach, and that the broader disease portfolio and development strategy should be evaluated before committing to a complex master protocol.

Yu Shyr, PhD, Dr(hc), FAACR, a professor at Vanderbilt University Medical Center, discussed statistical methods that may help identify treatment benefit earlier in a trial and with greater efficiency, potentially reducing sample size requirements and improving patient selection.

During a panel discussion, the group also considered the potential of seamless trials—where different clinical stages (phase I/II or phase II/III) are combined into a single trial protocol—rather than requiring a new study at each transition. Steven H. Stein, MD, executive vice president, chief medical officer, and head of late-stage development at Incyte, noted that several of the fastest drug development programs incorporated seamless phase I/II designs, helping reduce delays and accelerate the generation of evidence.

Cong Chen, PhD, scientific assistant vice president at Merck & Co., Inc., described similar advantages for seamless phase II/III trials, which allow researchers to gather additional evidence before advancing to confirmatory testing. These designs can support better informed decisions and reduce time and resources needed to bring new therapies forward.

AI and Data-driven Development

Artificial intelligence (AI) emerged as a recurring theme, with participants exploring how it could make clinical trials faster, smarter, and more efficient.

Ravi B. Parikh, MD, MPP, a medical oncologist and associate professor at Winship Cancer Institute of Emory University, showed how AI could streamline clinical trial design. Drawing on his own experience developing trial protocols, he described the process as time-consuming and repetitive, with limited standardization often causing multiple rounds of revisions across separate documents.

To speed up this process, Parikh developed a multi-agent AI system designed to support clinical trial design. Rather than a single AI model, the system uses several specialized agents to extract key study information, review literature, propose trial designs, draft protocol sections, and check for consistency. Parikh said the long-term goal is to replace handwritten protocols and intermediate documents with computational protocols, leading to more standardized trial design and faster study activation.

Digital twins are computational models that simulate aspects of a patient’s disease or response to treatment. Ravi Radhakrishnan, PhD, a professor at the University of Pennsylvania, led a breakout group focusing on this specific topic. “The term is a bit misleading. It can set a false set of expectations that it’s an exact replica of a patient. It’s not. It’s a twin of the process by which you make a decision,” he began.

Specific examples where this tool can be used in the drug development pipeline include dose selection and timing, patient selection, trial design, and safety. Digital twins can be particularly valuable in helping to choose drugs and drug combinations, which directly impact individual patients. Participants examined the pros and cons of the approach and emphasized that even if the models aren’t perfect, they add tremendous value provided their error rates can be quantified and fall within an acceptable threshold.

However, these tools are only as useful as the data and validation behind them, reasoned Radhakrishnan. For these models to make reliable long-term decisions, they need access to high-quality longitudinal real-world data. To trust their outputs, standards must be established within companies or academic settings and across the broader community, with alignment and acceptance from regulators.

Faster and More Meaningful Endpoints

Overall survival and progression-free survival remain important endpoints in oncology clinical trials but measuring them can take years. Participants in another breakout group, headed by Christy L. Osgood, MD, supervisory associate director for the Division of Oncology 1 at the FDA, explored ways to identify earlier indicators of treatment benefit that could accelerate drug development and inform regulatory decisions.

Patient-reported outcomes were one area of discussion, particularly with their potential role in dose optimization. Information reported directly by patients can help researchers assess treatment tolerability. Yet Osgood stressed that collecting this information requires careful consideration as it could potentially add more work for patients.

The utility of circulating tumor DNA (ctDNA) was also widely discussed, with participants noting it as a promising but still developing tool. By detecting tumor-derived genetic material in blood, researchers can learn about treatment response. Before ctDNA can be widely adopted as an endpoint, however, researchers must establish how best to use and interpret it, and doing so will require substantial supporting data.

Osgood recognized the significant time and effort required for the FDA to consider novel endpoints like ctDNA acceptable. Looking ahead, she proposed a path forward. “The first step is education about how regulators, drug developers, patients, and providers view these endpoints. The next step is bringing these groups together so we can work collaboratively to address the challenges.”

Bringing Trials Closer to Patients

A topic that dominated one of the panel sessions was how to expand clinical trial participation beyond major academic medical centers and into community oncology practices so more patients can access investigational treatments.

The group agreed that the community oncology gap is a major barrier to faster drug development, while acknowledging the challenges these sites face. Trial startup can be slow, and participation is expensive and time-consuming. As a result, many patients treated in community centers have limited access to clinical trials.

The roundtable discussed a range of solutions aimed at addressing hurdles for both patients and providers, including simplifying eligibility criteria and reducing the administrative burden associated with trial participation.

The conversation also highlighted the importance of patient navigation programs. In addition, participants suggested that financial and institutional incentives could encourage physicians to incorporate clinical trials more consistently into routine cancer care.

Precision Medicine: Getting the Right Drug to the Right Patient Faster

The precision medicine session began with a presentation from Anthony Letai, MD, PhD, FAACR, director of the National Cancer Institute (NCI). He discussed functional precision medicine, which he described as an overlooked approach to predictive biomarkers in oncology.

While tumor sequencing has transformed oncology by allowing clinicians to identify actionable mutations and match patients to targeted therapies, genetics often do not tell the whole story. Two patients with the same mutation can respond very differently, while some patients without an obvious biomarker may still benefit from a therapy.

Functional precision medicine approaches, on the other hand, can help overcome this challenge by capturing biological factors that are difficult to infer from genomic data alone, including epigenetic states, signaling pathway activity, and adaptive resistance mechanisms.

Letai described the potential of functional precision medicine through dynamic BH3 profiling, a functional assay that directly measures whether cancer cells undergo apoptosis after drug exposure. Rather than predicting response from a tumor’s genetic makeup alone, the assay evaluates how living cancer cells actually respond to treatment.

Because dynamic BH3 profiling can be performed within 24 hours, it has the potential to rapidly identify patients most likely to benefit from a therapy and support more efficient clinical trial enrollment, Letai explained.

Letai outlined the next steps for advancing functional precision medicine. He plans to establish a laboratory at NCI Frederick to lead an intramural effort focused on testing functional precision medicine as a predictive biomarker and using it to guide treatment selection for patients, while also enabling discovery-driven research. He would also like to support a nationwide extramural effort by coordinating centers across the country that are already conducting this type of work.

Lillian L. Siu, MD, FAACR, a medical oncologist and professor at Princess Margaret Cancer Centre in Canada and AACR Immediate Past President, expanded on the role of biomarkers across the drug development continuum, emphasizing the importance of incorporating predictive biomarkers early in development. “In 2025, of the 16 FDA-approved novel oncology drugs, 10 involved biomarker-selected populations,” she stated. Siu hopes this trend continues with the goal of building a path to use predictive biomarkers for every therapy.