A Landscape of Artificial Intelligence (AI) In Pharmaceutical R&D

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Pharma R&D Outsourcing


Contract Research Organizations Tap Into AI To Increase Value Proposition

   by Andrii Buvailo    450
Contract Research Organizations Tap Into AI To Increase Value Proposition

A few decades ago, pharmaceutical giants did most of the discovery work in-house, along with every other work necessary to get a drug or medical device to market. Nowadays, nearly any type of R&D or regulatory filing work that a drug maker or a medical-device producer needs to do -- from pre-clinical development to running clinical trials and go-to-market activities -- can be outsourced to CROs, and often it is the case.

According to a report by Kalorama Information, a market-research publisher in Rockville, Maryland, more than one-third of all global drug-discovery research will be outsourced to CROs by 2021.

In the wake of "the artificial intelligence (AI)-revolution" in the pharmaceutical and healthcare industries, CROs are tapping into various AI technologies to further cement their position in the global pharmaceutical R&D market -- in some instances competing for expertise and talent even with the leading drug makers.

Findings published by Deep Pharma Intelligence, a pharmaceutical industry think-tank in London, United Kingdom, in their report "AI for Drug Discovery, Biomarker Development and Advanced R&D Landscape Overview 2020" reveal that some of the leading CROs are actively adopting various artificial intelligence (AI) technologies, including machine learning (ML), deep learning (DL), and natural language processing (NLP) in their research workflows -- via building in-house platforms, or partnering with AI-vendors and AI-focused biotech startups. 

Since the overwhelming majority of CROs are involved in clinical-stage projects, most AI-involving projects are primarily dealing with such use cases as patient recruitment for clinical trials, clinical trial management and result modeling, and patient stratification. However, notable areas of AI application include early drug discovery, preclinical development, and pharmacovigilance.   

Arena International Announces the Brand New Direct-to-Patient and Virtual Clinical Trials Digital Experience

   by Kadin Luong    259
Arena International Announces the Brand New Direct-to-Patient and Virtual Clinical Trials Digital Experience

London – Arena International announced today the first-ever Direct-to-Patient and Virtual Clinical Trials (https://arena-international.com/dtpvirtual/) will be held as a Digital Experience on Thursday, 9 July 2020. As COVID-19 has forced the market to move towards decentralized and remote models, this event provides the perfect opportunity for clinical trial professionals to hear, meet and learn from top-class speakers around the world to discuss challenges and innovations in this critical time.

The Evolving Pharma R&D Outsourcing Industry: A Bird’s-eye View

   by Andrii Buvailo    7739
The Evolving Pharma R&D Outsourcing Industry: A Bird’s-eye View

Pharmaceutical companies are increasingly outsourcing their R&D activities, including early-stage research programs, to third party organizations -- academic institutions, biotech startups, and private contract research organizations (CROs) -- as a means to stay competitive, flexible, and profitable against all odds.   

Economically, there are factors such as increasing downward pressure on drug pricing by governments, an impending “patent cliff” threatening $198 billion worth of sales during 2019-2024), and downturns in income due to the increasing competition from generics and biosimilars. 

From the innovation's point of view, there is a boom in life sciences, stimulating the emergence of novel biological targets, therapeutic modalities, and even whole new areas of drug discovery -- adding opportunities, but also complexity and uncertainty to research programs. In fact, according to Deloitte’s report, return on late-stage pipelines dropped for the top 12 pharma companies from 10.1% in 2010 down to 3.7% in 2016.

Technologically, there is an unfolding “digital revolution”, bringing even further complexity and investment cost to the table -- in a form of artificial intelligence (AI), data mining and big data technologies, data-driven diagnostics, and digital health. 

Finally, the rise of the personalized medicine paradigm forces companies to rethink their research pipelines and “one-size-fits-all” product development programs, as well as reconsider their market strategies.