Improving Clinical Attrition and Decision-Making with Artificial Intelligence
About this webinar
This webinar will illustrate how technology can ensure researchers get a thorough, bird’s eye view of all available evidence, enabling faster, better-informed decisions from target identification through to Phase III clinical trials. This decreases clinical attrition, saves businesses a huge amount of time and money and ultimately brings more lifesaving medicines to market.
It is well documented that only 10 percent of clinical candidates make it to market. This is a startlingly low figure, especially when millions of dollars and years of development that go into a single candidate are taken into consideration.
The reasons for failure are known, with one of the most critical being poor target validation in the early stages of drug development. It has been shown that success rates increase when better informed decisions are made early on. To improve clinical attrition, it is therefore imperative to improve decision-making in R&D.
Artificial Intelligence (AI) has been transformative for many industries such as banking, automotive and transportation. Drug development however has not been impacted to the same degree. This is in part due to the drug development process being lengthy and complex, making it inherently difficult to integrate innovations. However, by using AI to influence key decision points along the R&D value chain, it is possible to unlock technology’s real value.
Register to learn how AI can augment and empower humans to make better quality decisions in R&D, leading to improved clinical attrition.
Who should attend
Professionals working in the drug R&D value chain with relevant job roles in the following areas:
- Target Identification/Validation
- Drug Discovery
- Biomarker Discovery
- Preclinical Safety
- Digital Transformation
What you will learn
In this webinar, attendees will learn:
- The impact of clinical attrition, and the reasons why it is so high
- How AI can read and digest information from millions of biomedical documents, extract key insights and present researchers with a complete view of the data
- How integrating AI into key points in the R&D value chain can improve decision-making and lower attrition — thus saving huge amounts of time and money
Featured Speakers
Richard Harrison
Richard has 35 years’ experience in pharmaceutical research and consulting. Previously he worked at Accenture, where he was a Senior Manager in the research domain and was responsible for IT solutions and platform innovations for pharmaceutical clients. Richard also worked as Chief Scientific Officer at Thomson Reuters (later Clarivate Analytics) and has pharmaceutical research experience spanning across companies such as Merck, Aventis and Novartis. In addition, Richard was a founding scientist in two biotech companies, and holds a PhD in physical organic chemistry from Rutgers University.
Mike Rea
- CEO and Founder of IDEA Pharma and Protodigm
- Pharma innovation protagonist, antagonist, and geek
- Author of “Positioning Pharmaceuticals” and a contributor to Fortune, STAT, and Endpoints
- Recognised as an industry influencer
- Global Power List: 20 in 2020, 2021 and 2022, the Top 20 inspirational medicine makers in biopharmaceuticals (The Medicine Maker)
- Global Power List 100 (Medicine Maker, the 100 most influential people in healthcare, 2017, 2018, 2019)
- Top 10 Innovators in Pharma (PharmaPhorum)
- PharmaVOICE Red Jacket: 100 Most Inspiring People in Healthcare (2011, ’13, ’15 and ’16, + lifetime Red Jacket award)
- The Medika Life 50 – The Most Influential Voices in Healthcare for 2022
- Senior Fellow at the Milken Institute
- Advisor to BioEthics International
- Strategic Innovation Advisor at Nanoform
- Created the industry standard annual Pharmaceutical Innovation and Invention index in 2010
Partner for this event
Causaly
Founded in 2018, Causaly’s mission is to transform how humans can find, visualise and interpret biomedical knowledge. Causaly acts as an operating system for biomedical and health data that empowers researchers to effortlessly identify new research avenues and innovative drug development opportunities. Our technology mimics human reading, and digests tens of millions of documents into an Enterprise Knowledge Graph, allowing researchers and decision-makers to answer questions they can’t answer anywhere else. To learn more, visit www.causaly.com.
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