Recently there has been a lot of hype around Artificial Intelligence and how it will revolutionise industry and replace many current jobs. In this session I will give an overview of how AI algorithms can be applied within the context of competitive intelligence. As an example we will use the lens of the Pharmaceutical Industry and discuss case studies on how digital tools are being used in business development, product planning, portfolio optimisation and M&A. During the course of this session I will give a basic understanding of types of algorithms, how they are trained and the type of data needed for successful model development. We will also discuss how the algorithms themselves are only part of the solution - human judgement, strategic thinking and value assessment is also required and this together with new technologies can make for a powerful advantage. We will also discuss the future of AI systems as we move towards a culture where machine intelligence is given a seat at the table for strategy and decision making.
Ketan Patel has 15 years of experience working in the pharma industry at Lilly, Pfizer, Oracle HSGBU and most recently at Astrazeneca. Ketan studied computer engineering and AI (MSc from Edinburgh), after which he did a PhD in Bioinformatics (Oxford). Over the years Ketan has led and worked on data science projects in the pharma industry from early stage drug discovery through to clinical development, product launch and medical affairs. At Oracle Ketan worked in pre=sales before moving to product strategy for Precision Medicine applications. More recently he was a Health informatics Director working on Big Health data (claims, EHRs, digital, genomics etc.) for AZ to optimise clinical trials, product launch and post-marketing and life cycle management. In his current role Ketan leads a product development team at Clarivate Analytics working on digital products that help biopharma and medical device companies with competitive intelligence, forecasting and market data. The products are increasingly making use of machine learning algorithms to increase utility for the customer.
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