Improving Efficiency Within Pharmaceutical Research and Development
Pharmaceutical research and development (R&D) is facing mounting pressures to improve efficiency, reduce costs, and accelerate the time it takes to bring new drugs to market. Historically, developing a new treatment has been notoriously slow and expensive, often taking 10 to 15 years and costing upwards of $500 million. Alarmingly, the attrition rate for drug development has remained at approximately 90% for several decades, primarily due to lack of efficacy or toxicity issues.
New technologies are now at the forefront of changing this scenario. One notable advancement driving efficiency is the introduction of multiomics technologies, which allow researchers to characterize various biological pathways and pinpoint key drug targets. According to Terry Kenakin, Professor of Pharmacology at the University of North Carolina, "The choice of target now becomes more important than ever because we can’t pursue all possible avenues. There are maybe 800–1,500 viable human targets out there, but industry can realistically pursue only about 350." This highlights the significance of selecting the right target early to prevent wasted resources.
Technologies such as spatial biology and mass spectrometry imaging are aiding this target validation process. While spatial biology preserves the cellular environment to provide insights about molecular interactions, mass spectrometry helps measure the abundance of metabolites across tissues. Consequently, these tools assist researchers to gain clearer perspectives on disease mechanisms, leading to informed decisions on where to invest time and resources.
Once these targets are identified, determining the therapeutic approach is the next challenge. Innovations in antibody and peptide engineering have enabled researchers to develop drugs targeting previously deemed undruggable pathways. For example, advances have led to the creation of drugs mimicking glucagon-like peptide 1 for diabetes and obesity treatment, which stalled for years before recent technological improvements.
Efforts to expedite drug screening have also transformed thanks to DNA-encoded libraries, allowing for large-scale screening of chemical compounds efficiently. This process now enables researchers to analyze millions of potential candidates within days, utilizing small amounts of the target. With screening processes improved significantly, researchers can now focus on differentiators among candidates before entering clinical trials.
The need for efficiency extends to patient recruitment and trial design, often hampered by poor tactics and insufficient planning. Jimeng Sun, Computer Scientist and AI application expert, identifies many hurdles within the clinical trial process. "From trial design to regulatory submission, there is much room for improvement. We are utilizing artificial intelligence to analyze historical trial data, aiming to predict outcomes for future trials and streamline recruitment processes," he states. Such predictive models can help make informed decisions about participation criteria and site selection.
Brian Powl, CCO of Kura Oncology, emphasizes the importance of collaboration across diverse expertise right from the drug development process's onset. He asserts, "Collaboration is key to drug development. The earlier it starts, the more favorable the outcomes. Engaging various cross-functional experts early on can prevent major gaps and mismatches between clinical trials and patient needs." This holistic approach ensures participant input is integrated, enhancing the drug development process.
Patient-centric strategies have gained traction, particularly as organizations recognize the importance of aligning trial processes with patient experiences. By involving stakeholders from not only the clinical and preclinical domains but also commercial development and advocacy, the industry can more accurately design trials to meet the needs and expectations of patients.
AI, particularly natural language processing, offers another avenue to improve recruitment and retention. Christina Brennan from Northwell Health highlighted the potential for AI tools to refine patient searches based on clinical history, enabling earlier identification of participants. They face deviations from traditional methods, showing initiative to pull from community identifiers when designing trials.
To facilitate smoother patient interactions, many organizations acknowledge the need for clear, straightforward communications during recruitment. A significant barrier to participation consistently remains excessive medical jargon and information overload. Simplifying the onboarding process can improve patients' willingness to participate. By adopting principles from business-sector best practices, such as gradual engagement and building positive identity around trial participation, protocol designs may evoke greater interest among potential participants.
TransCelerate BioPharma, committed to enhancing clinical trial efficiency, will lead discussions at the upcoming SCOPE Summit 2025. Their strategic vision emphasizes the convergence of clinical care and research as pivotal for future developments. “We are determined to advance R&D globally, address systemic challenges, and promote collaboration,” stated Janice Chang, CEO of TransCelerate.
Future innovations hold immense promise for enhancing the drug discovery process. By incorporating insights from collaborative efforts, advanced technologies, and patient-centered designs, the pharmaceutical industry may finally begin to reshape its developmental timelines and improve efficacy metrics. With sustained attention on these fronts, the hopes of revolutionizing patient access to effective medication might shift from aspiration to reality.