The predictions for 2024 further emphasize the importance of data, in both structured and unstructured formats, while also touching on a range of other themes related to everything from pharma partnerships with virtual care providers to the challenges and strategies in implementing the 340B drug discount program. In addition, our latest batch of predictions project an expansion in the use of synthetic data in drug research and development, particularly for overcoming barriers in accessing real-world data from patients’ electronic health records.
1. Pharma companies forge partnerships with virtual care providers
In 2024, pharmaceutical developers will seek out more partnerships with virtual care providers, predicts Dr. Lyle Berkowitz, CEO, KeyCare, the nation’s first Epic-based virtual care company. “Pharma companies face challenges educating large numbers of office-based providers on new drugs that may have niche markets,” Berkowitz said. Virtual healthcare companies offer pharma companies the ability to educate a smaller group of providers who can take care of patients via a national online platform. “This will ensure patients have a convenient option to get new prescriptions from experienced providers” via online consultations, he added. “What will also be critical is making sure the providers work on a system that is coordinated with the patient’s home health system to support quality care.”
2. Challenges and innovations in implementing the 340B drug discount program
As a result of ongoing data silos and a recent court ruling, the 340B drug discount program, which provides discounted medication to health care organizations serving vulnerable communities, will continue its rapid ascent in 2024, and safety-net hospitals will face new challenges in their efforts to implement compliant 340B programs, noted Angie Franks, chief executive officer of Kalderos, a data infrastructure and analytics company. “In addition, the burgeoning 340B program will make it more difficult to prevent duplicate discounts with MDRP (Medicaid Drug Rebate Program) and commercial rebates, and the program’s benefits to patients and the cause of health equity may suffer in the process,” she said. “Safety-net hospitals (also known as covered entities) and drug manufacturers must collaborate to create an industry standard framework for prioritizing which CE should receive the 340B price when multiple CEs consider a patient their own.”
3. NLP continues to support regulatory compliance
Jane Reed, director of life sciences at Linguamatics, an IQVIA company specializing in healthcare natural language processing (NLP)-based AI platforms, highlights the frequently changing nature of regulatory guidelines and regulatory data, which sometimes continue to create challenges for drug developers. “To maintain compliance with constantly shifting regulations, pharmaceutical companies need tools that enable them to discover, highlight, and extract key data within regulatory documents. NLP technology, which involves computer analysis and understanding of human language, is particularly beneficial to accomplishing these tasks, due to its ability to transform free, or unstructured, text in documents and databases into normalized, structured data suitable for analysis,” Reed said. “Combining different types of NLP (deterministic rules-based NLP, transformer models, LLMs for generative text) enables teams to use the right tool for each task, bringing most benefit from these innovations.”
4. Synthetic data set to take off in drug research
Moran Beeri, chief of global customer success at MDClone, a specialist in data analytics and synthetic data, emphasizes the growing necessity for drug developers to access real-world evidence (RWE), based on real-world data (RWD). She notes, however, that RWD found in patients’ electronic health records (EHR) is often confined to structured variables, capturing just a minuscule portion of the necessary detail for comprehensive drug research. Beeri underscores the potential of the expanded use of synthetic data. “By utilizing synthetic data, we can anonymize patient information while simultaneously exploring a wider array of both structured and unstructured data variables,” Beeri explains. This approach, she argues, is crucial for overcoming the current limitations in EHR systems and for advancing drug research, given that it allows for data anonymization and the exploration of both structured and unstructured data variables.”
5. Data-driven initiatives transform drug development processes
In drug development and discovery, 2024 holds immense promise in terms of harnessing data to drive medical and clinical research, according to Dr. Oleg Bess, co-founder of 4medica, a provider of real-time clinical data management and healthcare interoperability software and services.
Data-driven initiatives will play a pivotal role in accelerating clinical trials, leading to the development of more effective drug therapies and improved patient outcomes, Bess predicted. Data analytics and artificial intelligence will also enable researchers to gain deeper insights into disease mechanisms, enabling them to design more targeted and effective therapies, he said. “This data-driven approach will not only expedite the drug development process but also enhance the precision and efficacy of treatments and improving patient lives,” he continued.
Filed Under: Data science, Drug Discovery and Development, Regulatory affairs