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The healthcare industry has generated a large amount of information on genome, environmental factors, lifestyles, etc. to provide optimal medical services to individual patients through comprehensive analysis.
National pharmaceutical and biotech companies have participated actively into the AI-based research for new drug development. The vast quantities of medical data can be applied in medical and pharmaceutical industry to accelerate global development of new drug.
In big pharma, many companies have already implemented and applied AI-based system for genomic information and medical data analysis in prediction of the mechanism and side effects of new drugs and selection of biomarkers for disease diagnosis and treatment.
|Global Big Pharma||AI Application|
• Collaboration with IBM Watson Health to develop Clinical Decision Support Systems
• Automated anesthesiology system using FDA approved SEDASYS system through machine learning
• Development of AI-based next generation surgical robotic system with Verb Surgical
• Ethicon, a medical device company in the J&J: Collaboration with Google on advancing surgical robotics
• Janssen, an affiliate of J&J: Collaboration with BenevolentAI; UK based AI company, to the development of the new range of drug candidates
• Genentech, an affiliate of Roche: Collaboration with GNS (Gene Network Science) Healthcare to find and validate potential new drug candidates using casual machine learning and simulation platform
• Acquisition of Flatiron Healthcare and Foundation Medicine for healthcare data accumulation; a company with the most advanced real-world evidence platform and a world-leading molecular insights company, respectively
• Collaboration with GE Healthcare to develop Clinical Decision Support system, improving individualized treatment options for cancer and critical care patients. (System integration with biomarker, tissue pathology, genomics sequencing portfolio)
|Pfizer||• Collaboration with IBM Watson Health to accelerate immuno-oncology research for drug discovery with Watson’s AI platform to support the identification of new drug targets|
|Bayer||• Collaboration on early research projects with Exscientia to leverage the potential of AI in drug discovery platform and drug design know-how to treat cardiovascular and oncological diseases.|
• $300 M investment in 23andME, a company has largest database of genetic and phenotypic information of more than 10 million customers, to develop new drugs
• Collaboration with the Univ. of California to exploit the gene editor for new drugs screening
• Acceleration of new medicine discovery by exploring how gene mutations cause disease with AI and machine learning group
|Novartis||• Collaboration with IBM Watson Health to explore development of a cognitive solution that uses real-world data on outcomes-based care in advanced breast cancer|
|• Collaboration aims to integrate Illumina’s sequencing systems for large-scale analysis of genetic variation and function and Philips’ IntelliSpace Genomics clinical informatics platform|
|• Investment in PierianDx to help empower leading health institutions and diagnostic laboratories to deliver evidence-based genomic insights for more precise patient care.|
In randomized controlled trials for evaluating safety and clinical utility of new drugs, there is a large gap in success rate as 40-80% and the high failure rate is also reported due to its difficulty in patient recruitment.
However, the AI-based system enables to access and mine electronic medical records (EMR) and publicly available contents, such as trial databases and social media and this would lead to identify suitable patients, ultimately leading to improving the speed and efficiency of clinical trials. As such, AI technology in clinical trial increase the success rate and bring cost-effectiveness and this will play a critical role in pharmaceutical industry. Following that, pharma-diagnostic partnerships would maximize the effect of drug development by a remarkable reduction in time, cost and failure rate.
Novomics aims to expand our business to the companion diagnostics market through partnerships with big pharmaceutical companies on our technology that power molecular diagnostics and companion diagnostics. Through the partnership, big pharmaceutical company would enable to shorten the timeline of clinical trial and accelerate the new drug development with identification of biological features of diseases.