Clarivate Plc (NYSE:CLVT), a global leader in connecting people and organizations to intelligence they can trust to transform their world, today released its annual Companies to Watch report. This year’s report identifies seven innovators trying to change the drug discovery and development paradigm by utilizing innovative artificial intelligence (AI) and machine learning (ML) technologies. Drawing on data and analytics from BioWorld, published by Clarivate, paired with analysis of drug benefits, financing, R&D activity and more, this report explores why Clarivate believes these innovators stand out and what makes them companies to watch.
Rapid innovation is occurring at key centres of excellence globally. The United States and Mainland China are leading the way in patent activity to use AI for drug discovery.1 Organizations in Mainland China recently outpaced U.S.-based patent activity in this area.2 India comes third, with all other countries having fewer than 200 filings.3 Researchers in these regions are integrating data sets to identify new treatment candidates that could change the therapeutic paradigm. Understanding publication history and creation of IP as benchmarks of early success and capabilities can provide guidance on the future potential of their inventions and best-fit investment or partnership opportunities.
The report highlights companies leveraging AI and ML to tackle a range of long-standing issues in drug development including capitalizing on the rapidly expanding healthcare datasphere, understanding the underpinnings of disease biology, and maximising the recent advancements in computing power. From identifying novel targets to simulating how drugs will function in the human body, these companies are combining innovative technologies with therapeutic area expertise and data sets of partners to deliver more effective and safer medicines to market faster. Clarivate believes this year’s Companies to Watch, are:
AQEMIA – a next-generation pharmatech company, which uses unique quantum and statistical mechanics algorithms to fuel generative AI to design novel drug candidates.
Auransa – an AI-native biopharma company which harnesses available data to discover highly intractable diseases with poorly understood biology, aiming to raise the standard of care for cancers by prioritizing both efficacy and tolerability in the drugs advanced through trials.
Enveda Biosciences – focuses on the natural world for drug discovery. Enveda Biosciences leverages a combination of ML, metabolomics and automation to identify bioactive, plant-based molecules of interest to overcome the challenges inherent to both synthetic and natural product–based small molecule development.
Pharos iBio – utilizes AI technology to develop treatments for refractory and rare diseases such as cancers and to identify novel therapies and repurpose existing therapies across the company’s eight lead candidates that are undergoing preclinical or clinical evaluation.
Quris-AI – combines patient-on-a-chip, AI and real-time nano-sensing technologies to predict the safety and efficacy of drug candidates in humans in a quick, effective and scalable manner.
Relation Therapeutics – uses high-resolution biology, ML and clinical insights to discover transformational medicines. Both computational and experimental technologies are incorporated to better understand human biology and the causes of complex diseases.
SandboxAQ – combines AI and quantum technology (AQ) to address some of the world’s biggest challenges, including drug discovery for complex, undruggable targets and the limited accessibility of fast, accurate, and cost-effective medical imaging.
Mike Ward, Global Head of Life Sciences and Healthcare Thought Leadership, Clarivate, said: “It is becoming increasingly clear that AI/ML is going to have a consequential impact on the discovery and development of new medicines. Many advances in AI/ML are taking place in young fast-moving start-ups and, in this report, we have sought to identify some of these companies that we believe might not yet have appeared on the radar screens at big pharma.”
Lynn Yoffee, Publisher, BioWorld said: “There are a lot of theoretical advantages AI will have related to the development of new human therapeutics, but BioWorld’s sources are confirming that the realistic nearer-term impact of AI is the ability to quickly find the molecules that will work. This is key, as it’s going to dramatically reduce the time it takes to bring candidates forward through clinical and regulatory reviews and, ultimately, help reduce the failure rate of new compounds.”
The substantial increase in scientific knowledge, IP and deal-making over recent years underpins the growing acceptance of the role of AI and ML in drug discovery and development. As an enabling platform, these technologies are poised to become an integral part of creating and delivering intelligence that will be key for strategic partnerships to maximize patient benefit and commercial success.
