Enhancing decision making skills through implementation of a blended learning ‘Dragon’s Den’ style workshop for undergraduate pharmacology teaching

Background and Aims: New medicines undergo extensive safety testing, so that potential adverse effects can be minimised prior to licensing. An unacceptable safety profile is a key cause for late stage attritition of candidate drugs, during clinical development. Evaluation of a candidate drug’s safety profile requires integration of complex scientific data, obtained within ethical/financial and regulatory frameworks. Examples of data acquired prior to clinical development include: in silico and in vitro toxicology, unintended target interactions and in vivo safety pharmacology, toxicology and pharmacokinetic (PK) data from animals. The ability to integrate such diverse and complex data, and provide rational, evidence based justification to proceed or halt a drug’s progression, calls upon advanced decision making skills. However, competence in expert decision making, in the absence of direct practical experience, can be challenging to teach - with students focusing on ‘right’ or ‘wrong’ decisions rather than understanding how hierarchical ‘scientifically justified decisions’ may arise from a particular scenario. In an effort to develop competence in expert decision making in drug safety evaluation, we have devised a 4 week active learning workshop, incorporating blended learning techniques at King’s College London

Summary of work: Lectures incorporating case studies, describing the types of data that are acquired during preclinical drug development and what the outcome measures mean, were initially delivered. Students were allocated into groups (&tld;5-7) and provided with data packs containing efficacy, toxicology, safety pharmacology and PK data for 3 similar hypothetical drug candidates under development, for the same indication. Video footage of a roundtable discussion in which scientists reviewed similar data was shown, and students were asked to comment on this using pre-set framework questions, in class. Groups were subsequently tutored by industry experts who provided instant feedback relating to data-driven decision making. Students then worked in their groups to develop a presentation outlining their conclusions as to which drug they would proceed. Data transformation and presentation was supported by separate face-to-face help clinics. Student groups then presented their findings, in a ‘Dragon’s Den’ style forum where industry and academic experts questioned their conclusions. They were assessed on their group work, final presentation, individual 500 word executive summaries and calculations exercises.

Outcomes: Student feedback was highly positive, with many suggesting that this approach “forced you to think” consolidating taught material and improving communication skills. From 2014 feedback (66/71 respondents): 97% would recommend this module; 68% said it helped inform them about career options; 95% overall student satisfaction. Students overwhelmingly selected the Dragon’s Den active learning exercise as the best aspect of the module and when asked about their confidence in data handling aspects (1 = not at all confident, 5 = very confident) the following scores were achieved: Handling PK data (av. 3.73); data integration (av. 4.1); confidence in simplifying large data sets (av. 4.16). Blended learning tools introduced in 2014 to enhance data handling skills improved student scores in the final exam numeracy question, which incorporated qualitative and quantitative elements: with 58% of students scoring an A grade (70%+) in 2015 versus 31% of students in 2013.

Discussion and conclusion: The educational aims of the course were met, with students displaying decision making skills and data integration proficiency in both the workshop and summer written exam. The format of this ‘Dragon’s Den’ summative exercise should be transferable to other modules where data handling, integration and advanced decision making are key learning objectives.Cell162(5)pp993(2015)