21 May 2019
The 2019 State of the Discovery Nation report offers a revealing insight into the current status of the drug discovery community in the UK, clearly indicating that companies are beginning to leverage technological advances to improve the drug discovery pipeline. The report is compiled from responses to survey questionnaires sent out to small and medium-sized enterprises (SMEs) in the UK by the BioIndustry Association in collaboration with the Medicines Discovery Catapult (MDC) to create a snapshot of the current situation. This is the second report of its kind and is focused on two key areas: artificial intelligence (AI) for drug discovery and complex preclinical cell models, or CCM.
SMEs are crucial in the drug discovery process, in terms of employment and the innovation that they bring to the process. In terms of clinical areas, cancer came out as the strongest, with almost half the SMEs analysed focusing on oncology and over 38 percent of drug assets in development aimed at this area.
The need for strong understanding of the biology of human cancer underpins calls for fit-for-purpose CCM, with core needs of predictivity, reproducibility, validation and ease of interpretation. CCM improve on traditional 2-dimensional culture models, introducing dynamic flow and three dimensional, differentiated tissue structures to create more physiologically accurate representations. The report notes: “The use of CCMs is being driven by a combination of decreased trust in the translational value of animal models and increased availability of data to support the validity of complex human cell models.” For these human-relevant models to take their place in preclinical research, potentially usurping the increasingly discredited patient-derived xenograft mouse models, increased confidence from users and regulators is required. However, it is promising that pharma companies claimed a willingness to share compounds for CCM makers to use in testing and validation experiments and the MDC could play a vital role in creating networks of suppliers and users, sharing information and best practice to enable acceleration of the acceptance and validation of CCM, and the ultimate replacement of animal models – saving money and lives.
AI is now recognised as a core component of the drug discovery, across all stages (lead generation, preclinical and clinical), reflected in growing AI budgets. It is encouraging that pharma are willing to try new models of data sharing, since data availability is a crucial component for enabling AI in drug discovery. These data sharing methods would need to reveal sufficient data for machine learning, whilst maintaining confidentiality of the identity of biological targets and compound structures. There are areas for improvement here as well, validation is important and could be achieved through the use of test datasets, pilot projects and other partnerships.
It is apparent that industry is beginning to see the promise of cutting-edge technologies such as AI and CCM for improving medicines discovery. With increased funding and dedicated support for these disruptive technologies, the UK could lead the world in human relevant drug discovery.