ARTIFICIAL INTELLIGENCE SHOWCASE Driving Drug Innovation With AI The global AI market has been showing rapid growth as major pharmaceutical and medical technology companies invest heavily in internal and external AI partnerships. ccording to some reports, more than key objective is to predict which patients are 50% of executives expect broad scale at risk of cardiovascular disease and then de- How Pharma Can Use A AI adoption by 2025. Further, reve- termine the treatments that might work best. nue generated through AI-based solutions in Scientists at Janssen Research & Devel- AI for Drug Innovation the industry is projected to rise at a CAGR opment have found a way to use AI to speed Create internal expertise and of 21.94% and reach $2.199 billion by 2022, the process of discovering new potential treat- according to Frost & Sullivan. Meanwhile a ments. They are using AI to sort through support AI employees with the right report by Global Market Insights forecasts how cells representing certain diseases react resources that the U.S. healthcare AI market will exceed to a variety of compounds. Then, through Collaborate with start-ups and $10 billion by 2024. With total investment collaborations with academic partners, they others using AI in drug discovery exceeding $7.2 billion across 300-plus deals are using computer algorithms to predict how Partner with academic groups that between 2013 and 2018, the pharmaceutical other cells are likely to react to those same focus on AI R&D industry continues to lead the healthcare sector compounds. The benefit for scientists is they in terms of attracting AI-related VC funding. don’t have to start over for every study, which Consider open science projects or The COVID-19 pandemic has propelled means they can potentially get treatments to various R&D challenges growth in AI investments with a new wave of patients faster. Source: A Guide to AI in the Pharmaceutical Industry, transformative technologies being developed Many other companies are partnering with Stefani Group in an effort to contain the pandemic, such as AI leaders to drive innovation. For example, smart machines and robots. AI is also being Pfizer formed a partnership with Atomwise put to use to determine the effectiveness of to help identify potential new drug targets by nology to find treatments that will mitigate existing drugs in the treatment of the virus. using deep neural networks toPharmaVOICE quickly analyze disease complications that arise during and millions of molecules. This further expands after infection. Its Project Prodigy platform Pfizer’s AI-led initiatives, which have included maps all known drugs against every possible Transformation Through AI partnerships with IBM Watson and invest- mechanism in which the COVID-19 virus ment in MIT’s Machineof Learning for Pharma- operates and causes complications, and seeks to Many pharmaceutical companies see huge ceutical Discovery and Synthesis Consortium. build scenarios to identify non-obvious medi- opportunities to transform their operations Other pharmaceutical companies have cal solutions as well as non-linear risks. with AI capabilities, from productivity im- formed partnerships with Atomwise to drive provements to better outcomes across the drug discovery, including Merck, Bayer, and value chain to using AI to create new offerings. AbbVie. In addition, AbbVie is working with Challenges to AI Innovation AI is top of mind for GSK, which an- AiCure to monitor medication adherence in nounced plans to recruit 80 AI specialists by patients with schizophrenia. One of the biggest barriers to growth in the end of 2020. The company’s AI head- One small biotech company that has been AI capabilities is the limited number of AI ex- quarters will be in San Francisco, but experts putting AI into practice in its drug develop- perts. According to a report by Tencent, there will be spread across Europe and the United ment process is Verge Genomics. The com- are about 300,000 AI researchers and practi- States. The goal is to use AI in the search for pany uses similar processes to those that power tioners worldwide but the market demand is treatments in various therapeutic categories, Google’s search engines to map out hundreds for millions of roles. Other barriers include including cancer and autoimmune diseases. of genes that cause disease, and from there regulatory pathways. Since innovation must The company is also working with several AI find drugs that target all the genes at once. By be balanced with safety risks, there is a need platform developers to advance drug discovery. using AI, Verge is taking products into clini- for robust strategies to enable well-considered Another company that is investing heavily cal trials rapidly thanks to its approach. For ex- market surveillance for AI-led innovations. in AI is Bayer. Together with Merck, Bayer ample, it is expected to start a small molecule AI is only as good as the innovators behind has developed the CTEPH Pattern Recogni- ALS program in 2021, followed by four more it, with experts noting that to deliver results, tion AI Software to help radiologists recognize programs. It has achieved this by building a users must ask the right questions and work chronic thromboembolic pulmonary hyper- massive database of brain tissue sequences. with clean data. In Verge’s case, the com- tension, a rare form of hypertension. FDA has Another biotech company committed to pany started its work in human rather than granted breakthroughCompliments designation for the soft- AI is Healx, which has created an AI platform animal models, combining its brain sequence ware, which will be deployed through Bayer’s for rare diseases. The company’s purpose built database with human genetics, overlaid with Radimetrics platform. AI platform, Healnet, serves to fill crucial gaps human-derived neurons. This let researchers In addition, Bayer is using a combination in knowledge about rare diseases and speed the identify gene signatures that appear in pa- of real-world data and AI-driven solutions to discovery of new treatments. tients. improve the characterization and stratification Another AI-driven bioscience company, Despite the challenges, the importance of (c) PharmaLinx LLC. Rights do not include promotional use. For distribution or printing rights, contact [email protected] of disease as well as patient populations. A Biovista, is applying augmented and AI tech- AI in drug development is now well-under- 24 October 2020 ● PharmaVOICE SHOWCASE ARTIFICIAL INTELLIGENCE EXECUTIVE VIEWPOINTS Rich Christie, M.D., Mike Weber On-Demand Reproducibility Ph.D. VP of Product Pharma companies work in a highly Chief Development Management regulated environment, and in addition Officer Aktana to using AI to drive data insights it AiCure is vital to ensure compliance with regulations, especially computer systems validation requirements. For this purpose AI Provides Patient Support It’s All About Balance traceability and reproducibility of data AI-powered solutions are playing a Implementing AI effectively is all about is key. Hence, being able to capture and pivotal role to keep patients engaged balance. The key is finding an AI partner reproduce on demand a trail of how in their trials, ensure visibility into their who excels at integrating all data an AI system predicted an outcome is well-being, and maintain communication assets, coordinating all stakeholders key. This places an additional onus on by providing multiple avenues of and leveraging existing technical and implementation and effective use of AI support. Sponsors of clinical trials and analytics investments. A well-rounded systems. sites need data mining and advanced AI implementation that can be deployed analytic capabilities to safeguard trials quickly, adopted effortlessly and can Jerome Premmereur, with meaningful insights and limited data generate practical suggestions and insights M.D. variability, especially when supporting for users allows the organization to focus VP, Patient Safety trials remotely. on agility, continuous improvement and Solutions and extracting the most value from their AI. Adjudication Michelle Marlborough PharmaVOICECovance Chief Product Officer Agility and Vigilance AiCure Production-grade AI models take work Time, Resources, and Quality to maintain. As markets shift, models AI is helping a lot in the equation of drift, especially in theof face of unexpected three variables that safety is dealing change, like COVID-19. Pharma companies with, wondering how we can get must establish a diligent practice of balance. The three variables are time, Enhancing the Patient Experience ingesting recent data, retraining AI models, resources, and quality. One cannot be Partnering with AI vendors that have and regularly evaluating their predictive perfect without sacrificing the other solutions that truly reach patients where health to ensure they haven’t degraded. two. Time is regulated and cannot be they are, and that use technology already Companies must also remember that as AI adjusted above the traditional reports at a patient’s disposal to enhance patient changes, so do the workflows of its users. of 7/15 days for expedited safety reports engagement will empower study teams This agility requires eternal vigilance, but (ESR). Resources are very substantial at sponsors, sites, and CROs to focus the competitive advantages that result can if the quality of the report is at the on the patient experience. Furthermore, be remarkable. level expected and on time. AI is fast. A this focus on partnering with technology learning machine on natural language vendors will also give study teams the Dinesh Kasthuril processing (NLP) can read hundreds of patient data visibility needed via a single Global Head, Client pages much faster than any physician dashboard to help them make data- Relationships and Project and can extract the elements that are driven decisions that can greatly impact Management important in a narrative for the ESR. the successful administration of an Covance Patient Safety Therefore, time, resources, and quality ongoing study.Compliments are able to achieve a new and better s stood.