2024 Pharmaceutical Industry Predictions

By Seema Verma - SVP and GM, Oracle Life Sciences

Integration With Real-World Data Will Be More Prevalent

Real-world data sources, which can include patient-reported outcomes, insurance claims data, data from wearable devices, and detailed patient histories found in electronic health records (EHRs) can provide a more refined understanding of treatments in real-life settings. This data will become pivotal in enhancing clinical trial execution, generating drug safety and efficacy evidence, and supporting drug reimbursement strategies.

Personalized Medicine Will Be A Focus

Using advanced analytics, machine learning, and computational power to glean insights from data, clinical research will continue to focus on ways to create personalized therapies for individuals’ exact conditions, not just general diseases. We expect to see a significant shift towards embracing the patient’s voice and ensuring that every stage in drug development is informed by the nuanced, real-life experiences of diverse patient populations.

Cloud and AI Adoption Will Help Close The Gap Between Clinical Research And Clinical Care

 Currently, clinical research is based on small snippets of health data, while many critical elements of patient clinical care data sit inaccessible and siloed. The industry is getting to a point where technology, cloud computing, data integration, and clinical care research can all be part of the same spectrum. As AI enables quicker analysis and faster insights, clinical research will become more accessible, cheaper, and more accurate because the information will be based on data that are more complete.

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 Back Page 2024 Pharmaceutical Industry Predictions By Seema Verma SVP and GM Oracle Life Sciences 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, and 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 shortly.

Decentralized (And Hybrid) Trials Will Become Normalized

The pandemic greatly accelerated the adoption of decentralized clinical trials (DCT). Now, things like connected devices and wearables have created an environment where DCTs have become and will continue to evolve as a viable option to collect needed data. This will lower the barriers to entry, expand access to trials, and enhance patient convenience. Look for clinical trial designs to strike a balance between traditional and DCT methods, and better incorporate the needs of the patient in the process.

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 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.

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