By Clinical Research Team 

January 3, 2024 | We spoke with leaders and experts in the Clinical Research community about their predictions for 2024. There are many anticipated developments in AI and machine learning, particularly in how it can support clinical trials. “In 2024, the pivotal factor for clinical trial success lies in the adept utilization of AI,” says Niven R. Narain of BPGBio. “After a year of several highly anticipated AI-designed drug candidates failing in clinical trials, this next year represents an opportunity for companies who have quietly continued to focus on biology, progressing in clinical trials with proprietary AI platforms and algorithms to step into the light.” 

We can also expect generative AI to help speed up the process of getting studies approved and ready to go, according to Francois Torche of CluePoints. “The last 12 to 18 months have seen a huge increase in activity around generative AI, which can create new content based on historical structured and unstructured data, including large language models (LLM): LLMs, such as ChatGTP, analyze and learn from large language datasets to predict what is likely to be the next word in writing an ‘answer’ to a given question. In the clinical trial space, companies have been using these models, for example, to design protocols and perform risk assessments, thereby shortening the time it takes to get studies up and running.” 

Clinical trials can also expect more diversity and inclusion, especially with the FDA’s new guidelines that will be implemented next year. Jaleeysa King of Greenphire says, “In 2024, I predict that the industry will prioritize and implement diversity action plans, as required by FDA guidance. This will lead to an increase in clinical trials that are more patient-centric, with solutions embedded to remove financial and logistical burdens which have historically caused increased patient dropout. We will see a more collaborative approach among industry colleagues to make patient-centric trials the norm rather than the exception.” 

Finally, as clinical trials continue to include a wider range of candidates and patients from different backgrounds, they are also working toward a more patient-centered model. “It is taking time for pharma to recognize and adapt, but a patient-first mindset will continue to affect the way trials are designed and conducted: This evolution will create significant improvements in clinical research, as sponsors and CROs make patient-centricity mean more than simply offering patients a blanket and transportation,” comments Steve Rosenberg of uMotif. 

Here are the full trends and predictions, including more information on AI and machine learning advancements, detecting and identifying biomarkers, women’s health, and data management. –the Editors   

Vincent Keunen, Founder and CEO, Andaman7 

Next year we will see patient-centered drug development evolve into patient-mediated research: The emergence of decentralized clinical trials and advances in how we can integrate sources such as electronic health records (EHR) from hospitals and patient-reported outcomes (PROs) have given sponsors a direct line to research participants. This will enable research teams to bypass the current lengthy process involving multiple actors, and will allow for faster, more cost-effective clinical trials. Tapping into this will also give developers a holistic view of how their products work in real-world settings, and, in combination with working with patient advocates, using software tools built by patients for patients, better understand what they want from their medicines. 

Niven R. Narain, Ph.D., President and CEO, BPGBio 

In 2024, the pivotal factor for clinical trial success lies in the adept utilization of AI: After a year of several highly anticipated AI-designed drug candidates failing in clinical trials, this next year represents an opportunity for companies who have quietly continued to focus on biology, progressing in clinical trials with proprietary AI platforms and algorithms to step into the light. We will see that AI is the accelerant we’ve needed to quickly analyze data and guide how we structure trials, offering better methodologies, better pathways, and more specificity to which patients to focus on so we can fail fast but ultimately succeed even faster in clinical trials. 

William F. Feehery, PhD, Chief Executive Officer, Certara 

The Inflation Reduction Act is causing disruption in the pharmaceutical market and creating opportunities, it provides a powerful incentive to find more cost-effective ways of developing drugs: We anticipate that many companies will look even more closely at the advances made in biosimulation technology and its increasing acceptance by the FDA in making important decisions regarding dosing, clinical trial designs, approval of generics, and label expansions. There is a huge opportunity to reduce cost and make better decisions - necessity meets opportunity. 

Francois Torche, Co-founder and Chief Product and Technology Officer, CluePoints 

The last 12 to 18 months have seen a huge increase in activity around generative AI, which can create new content based on historical structured and unstructured data, including large language models (LLM): LLMs, such as ChatGTP, analyze and learn from large language datasets to predict what is likely to be the next word in writing an “answer” to a given question. In the clinical trial space, companies have been using these models, for example, to design protocols and perform risk assessments, thereby shortening the time it takes to get studies up and running.  

Over the next year, we expect companies to move towards using generative AI models in other areas of trial design and conduct, including the creation of synthetic arms. This could be particularly useful in indications where a control group is hard to recruit or retain, such as rare diseases or those carrying imminent mortality risks. 

However, we also predict that the adoption of generative AI will raise as many questions as it answers. There is a danger, for example, of a widening gap between large companies, which have access to decades of historical data, and smaller or younger organizations, that will need to rely on less accurate public data to build their models.  

We also need to understand how to validate these new approaches, which continually learn from and refine their results. This is a concern that has already been flagged by international regulators, and we expect to see further discussion on how it can be addressed in 2024. 

Peter Smilansky, Senior VP, Product Strategy and Development, EDETEK, Inc. 

Top 20 pharmaceutical companies will initiate fewer clinical trials than they did in the last 3-5 years as many are facing financial hurdles or undergoing re-structuring, process optimization, etc.: There will be more M&As and supporting information technologies with flexible data integration capabilities will be important. 

Biotech companies will decrease funding of discovery and preclinical research and will spend more on clinical trials which will boost adoption of clinical technology -- especially among the most innovative companies with promising pipelines: We will see an increased focus on spending on the most promising clinical trials to expedite the data readouts to attract additional funding or to prepare companies for acquisition or IPO. Clinical informatics and study conduct technology vendors will provide more product or related functional services, such as compliant and secure multi-tenant platforms that require less time to implement, and with streamlined configurations and affordable study-based licensing. And sponsors will focus more on business valuable information consumption rather than using internal resources on technology learning, configuration and management. 

Development of AI/ML technologies for clinical research and development will continue: However, we predict its use will be more focused. AI/ML will help determine safety and efficacy profiles early to make go/no-go or adjustment decisions sooner by having comprehensive study insights easily available. AI/ML will deliver partial or complete automation of various study configurations, early detection of scientific and operational study abnormalities and production of readily consumable visualization and reports. Additionally, advanced clinical data review systems will begin to offer “ChatGPT style” conversational interfaces targeting scientific and operational business functions.  

Mark Kiel, MD, PhD, Chief Scientific Officer and Vice President of Product Strategy, Genomenon 

Clinical research: Biology became a data science in the early 2000s, with the advent of genomic sequencing. In the coming years, we will witness another transformative shift as pharmaceutical companies target more rare diseases, stratify clinical trial subpopulations using biomarker and genetic data, and rely on more structured and unstructured patient data from a myriad of sources. Tools that help clinical study teams organize and interpret this deluge of data will be critical, as will a source of truth to use as a benchmark. 

Jaleeysa King, Agile, Scrum Product Owner, Co-Chair All In Diversity Committee, Greenphire 

Diversity actions plans: In 2024, I predict that the industry will prioritize and implement diversity action plans, as required by FDA guidance. This will lead to an increase in clinical trials that are more patient-centric, with solutions embedded to remove financial and logistical burdens which have historically caused increased patient dropout. We will see a more collaborative approach among industry colleagues to make patient-centric trials the norm rather than the exception. Although we have had many conversations about the patient experience in the past, I believe that in 2024, we will see more of an adopted implementation of what we have learned over the years and make a global shift and impact for the patients we support in this industry.” 

Michael Rogan, Sr. Director, Mobile Application Experience, Greenphire 

Future of mobile in clinical trials: We know that participants really want to take part in clinical trials, but that isn't so easy to do. People may not be able to anticipate the kind of responsibilities that are involved, and what adherence to protocols really entails. It's important to be able to reach out to people in their everyday lives to assess how they are doing and find out what would help them succeed in their essential role as research partners. This is one area where mobile and web apps can help - and the challenge for clinical trial operations is to use these apps in ways that reduce participant burden, rather than just give them more things to do. The ability to use apps to assess participants, day by day, and provide the right kind of support so that consistent adherence is manageable - that is an important part of the future of web and mobile apps in clinical trials. 

Ariel Katz, CEO and Co-Founder, H1 

The FDA will enact laws that will supercharge diversity in clinical trials: In 2024, the FDA will finally pass legislation requiring Phase 3 clinical studies to meet specific diversity markers, aiming to ensure greater representation of diverse patient populations in clinical trials. 

Marc Buyse, ScD, Founder, IDDI 

Advances in computing power and the ever-growing focus on patient-centricity will drive the adoption of innovative trial design in 2024: Multiple study-specific efficacy and safety criteria can now be combined into a single aggregated measure estimating the net benefit of clinical treatment. Not only can this multi-criteria integration steeply reduce sample size (on average by 20%), but it also enables sponsors to design trials, including all objective criteria that matter to patients. With the multiple initiatives to elicit patients’ preferences in the development of new treatments, adoption of these innovative trial designs is set to become the new gold standard. 

Cyndi Verst, President of Design and Delivery Innovation, Research and Development Solutions, IQVIA 

Ever-changing regulatory landscape: Beyond broader macro-economic environment influences, clinical trial sponsors must stay on top of multiple evolving regulatory requirements worldwide. Trial programs are increasingly expanding across countries and sites, including new and underrepresented areas, ensuring those most impacted by a disease can participate and have access to treatment. This means existing regulations and guidance across regions are often updated, along with new requirements, requiring close monitoring to stay agile in strategy and revamp trial design and execution as needed.   

Globally, with increased integration of decentralized trial (DCT) elements, the International Council for Harmonization issued the draft Good Clinical Practice E6 (Revision 3) guidelines in May 2023 to better address DCT elements and related design requirements and ensure patients and data are protected. Also, in January 2024, the European Medicines Agency’s Clinical Trial Regulation 536/2014, which intends to provide a singular application submissions process across all EU member states, will be in effect for one year. Sponsors are navigating the intricacies of a complete overhaul in processes and guidance since the previous and longstanding directive, including training on the new submissions technology portal and related functionalities and communications with country regulators. In addition to this dynamic regulatory landscape, applicable local legislations are shifting, as well. For example, in the U.S., drug developers will need to closely monitor the impact of the Inflation Reduction Act on future research and development plans. 

Jason Dong and Sam Whitaker, Co-Founders, Mural Health 

The industry has been talking about the need to increase access to clinical trials for some time, but we are hopeful that 2024 looks set to be the year that we make a big difference: We now have integrated technology that enables flexible payments to clinical trial participants and eliminates fees, this particularly benefits underserved groups, such as those from lower income households and minority groups. As such the argument has moved away from whether sponsors should offer payments to cover the costs of participation, to how.   

Seema Verma, SVP and GM, Oracle Life Sciences

There will be a focus on patient optionality to create wider access to, and diversity in, clinical trials: In 2024, we will see a more concerted effort among trial providers to make it easier to connect patients and providers with clinical trials. For doctors and patients, continuing to enable access to diverse health systems that share de-identified data to fuel research and connect patients with viable trials will help to accelerate the discovery, development, and deployment of groundbreaking insights and therapies. Community-based settings, such as commercial pharmacies, small community hospitals, and even pharmacies at local grocers will provide more trial sites and create broader, more diverse access for patients across socio-economic backgrounds and geographies.

Generative AI will make its mark: Generative AI will begin to transform every phase of drug development, driving efficiencies across discovery, clinical trials, and safety through automation, optimization, and advanced insights. LLMs will enhance our understanding of biology and molecular screening, improving the speed and quality of early preclinical drug discovery pipelines that can help unlock new therapies. Generative AI can also play a crucial role in clinical trials by identifying diverse patient populations, optimizing trial designs, integrating numerous data sets—including genomics, EHRs, and RWD —to increase patient recruitment and trial success rates. We may even see generative AI help us get closer to making fully digital protocols a reality in the near future.

Xoli Belgrave, Senior Director, Head of Clinical Trial Diversity & Inclusion, Parexel 

Looking ahead to 2024, we encourage the industry to continue prioritizing overcoming racial, ethnic and cultural disparities in the clinical research industry and promoting diversity in clinical trials: The industry and regulators are likely to consider that as people, patients live with multiple intersectionalities. Factors like socioeconomic status, gender, ability, or geography that may impact an individual’s willingness or ability to participate in clinical research need to be included in conversations about patient inclusion and we expect this conversation in more forums in 2024. We anticipate a continued increase in industry-wide DEI initiatives, with CROs and other organizations placing a greater emphasis on diversity and inclusion in their clinical trial processes. This may include the implementation of specific goals and metrics to measure diversity, as well as the establishment of dedicated DEI teams or positions within these organizations. To address the challenges of patient diversity in clinical trials, strategies to enhance patient recruitment and retention rates will be critical. This may involve targeted outreach efforts to underrepresented populations, such as community-based events and educational programs, as well as the provision of language and culturally appropriate materials and resources. It will also be important to address barriers to participation, such as lack of transportation or childcare, through the implementation of flexible trial designs and the use of telemedicine and remote monitoring technologies. The industry as a whole will continue to push for greater diversity in clinical trials to ensure that study results are applicable to the broader population. 

Stephen Pyke, Chief Clinical Data and Digital Officer, EVP Clinical Data & Digital Services, Parexel 

AI is not a new technology: It has certainly been around since the 1950’s and in recent years has been deployed for many use cases across the medicines lifecycle in drug development. However, there is no question that there has been a marked upswing in interest to deploy in clinical development since the emergence a year ago of Large Language Models, which substantially reduce the “cost of entry” for developing AI-based tools. In Clinical Operations, the areas of application highlighted above will no doubt see deeper, more sophisticated, and more integrated AI solutions emerge in 2024, with the first ‘platform solutions’. For instance, we are beginning to see first generation tools that can generate a draft protocol, learning from relevant past examples, incorporating study feasibility considerations based on eligibility criteria. This can be linked in turn to study launch planning (country and site selection), again with a view to optimizing operational aspects. Connectivity to enable a draft database build is also created. And so on. I’m sure we’ll see much further development in this space in the year ahead. Similarly, the already extensive development of AI-based tools to support adverse event case processing will extend seamlessly into signal management as well as signal identification tools. 

Graham Clark, CEO, Phastar 

Artificial intelligence (AI) has already started to change research, and in 2024 we will need to be ready to understand and respond to the way it will change the role of data analysts: The profession has already started to evolve to one of data science, but many questions, particularly around education and progression, still need to be addressed. How, for example, will data analysts become data scientists if much of the entry-level work such as data sorting is performed by algorithms? Moreover, how can organizations such as CROs clearly communicate AI-derived insights to their sponsor partners in a way that can inform decision making? We expect such conversations to intensify, and lead to solid solutions, in the coming year.  

Steve Kearney, Global Medical Director, SAS 

Generative AI evolves to bolster clinical care: Health and life sciences organizations will further develop generative AI-powered tools in 2024 for personalized medicine, such as the creation of patient-specific avatars for use in clinical trials and the generation of individualized treatment plans. Additionally, we will see the emergence of generative AI-based systems for clinical decision support, delivering real-time guidance to payers, providers, and pharmaceutical organizations. 

Christian Hardahl, Global Health Care Solutions Manager, SAS 

Patients push to own their data: Patients will increasingly demand to own their health and social data and only make it available to the resources they choose. As such, patients will have more autonomy in choosing their specific care teams and seeking out multiple care experts to identify the best treatment paths. At the same time, patients will expect increased security and handling of the personal data they share, and the personal data that health care and pharmaceutical organizations access.   

Health organizations lean into AI governance for regulatory adherence: In 2024, health organizations will focus on compliance to AI regulations like the EU AI Act and FDA framework. To ensure the safety and trustworthiness of health AI tools and prevent regulatory hurdles that might hinder progress, organizations will lean into AI model governance practices such as data linage, traceability, model documentation, re-producibility, versioning, signing, and GxP for health care environments.  

Steve Rosenberg, CEO, eCOA/ePRO platform provider uMotif  

It is taking time for pharma to recognize and adapt, but a patient-first mindset will continue to affect the way trials are designed and conducted: This evolution will create significant improvements in clinical research, as sponsors and CROs make patient-centricity mean more than simply offering patients a blanket and transportation. I see three specific areas for improvement. 

First, involve patients in trial design and development to reap the benefits of giving patient advocates a stronger voice in influencing how studies are designed and rolled out. Second, address patients’ increasing expectations for patient reported outcome technology by giving them apps are akin to those they use in their personal lives. Third, eliminate silos. Sponsors and CROs can keep patients engaged for the duration by keeping them better informed, including sharing their data with them throughout the trial, and returning it to them at the end. And one last point—I've been preaching for a long time now that we need to treat clinical trial participants like the heroes they are. They're making a huge sacrifice in time and body and effort.

Richard Young, vice president, Veeva Vault CDMS strategy

Holistic data management will help sponsors deliver complex studies more efficiently: As the complexity of clinical research increases sharply in the coming years, we will realize new operating models for patients, sites, and sponsors. To deliver new data and user journeys that connect all clinical research contributors, we will call time on disconnected tools and embrace the platform era.

In previous decades, the industry addressed challenges by throwing resources at every problem. When that didn’t work, we created burdensome point solutions that lowered productivity. Sponsors undertaking today’s complex trials, including in gene and cell therapy, will need data-driven connectivity so patients can participate effectively and trial data can be reviewed and actioned in real-time. This is only feasible when all relevant data can be managed on the same platform.

Data will be distributed across research participants in a controlled and appropriate manner. Instead of silos, each data point will automatically initiate the next step in clinical trial execution. Humans will remain in the loop even while there is less need for manual intervention and facilitation. This new level of connectivity will drive science forward by providing the flexibility to work with diverse, distributed, and exponentially growing data sources.

Amy Abernethy, President of Product Development and Chief Medical Officer, Verily 

In 2024, we’ll make meaningful progress towards reshaping clinical trials by connecting them to the care experience and integrating data from sources such as wearables and the EHR: With participant consent, this will allow us to build a comprehensive, longitudinal view of their health journey through time. This will not only enhance the quality of clinical research, but also help us to better understand the effectiveness and safety of treatments in broader and more diverse patient populations. Additionally, the user experience will be streamlined, with technology reducing the burden on patients and making trials more accessible. It's a vision of a future where trials are not just more efficient, but also more inclusive and patient-centric. 

Geoffrey Gill, Founder and CEO, Verisense Health 

We will start to see widespread sharing of precompetitive data from wearables and other digital health technologies: The arguments for sharing precompetitive digital health data are so compelling that they will finally overcome the instinctive reluctance of pharma companies and researchers to share anything that seems like intellectual property. The winning arguments will center around the need to start standardizing digital biomarkers and to provide a unified perspective to regulators and payers. Furthermore, the amount of data required to effectively use AI is far too large for even the largest pharma company to collect on its own.