Table of Contents:
Introduction
The abundance of venture capital, major funding rounds
New AI-driven biotech startups founded in 2020
Notable AI-focused collaborations involving “big pharma” players
AI adoption by the contract research organizations (CROs)
AI-designed drug candidates in clinical trials
The emerging role of AI tech in fighting COVID-19
The Report, by Deep Pharma Intelligence, Features Strategic Insights About Pharmaceutical AI Sector Including Analysis of 1000+ Biotech Startups, Investors, Corporations and R&D Hubs
How AI and the European Health Data Space will revolutionise evidence generation in life sciences
FREE WEBINAR | Thursday 10th December | 1400 London / 1500 Paris / 0900 New York
R&D & Clinical Processes for the Future: Accurate, Efficient & Cost-Effective
The AI-ML: Drug Discovery Summit is the industry’s definitive guide to translating the wealth of tech available to successfully implement a working and practically effective drug discovery and development platform.
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.
