In the relentless pursuit of improving healthcare and finding new treatments for diseases, the pharmaceutical industry has embraced a powerful ally: Artificial Intelligence (AI). This technology is transforming the way drug discovery is conducted, making the process faster, more efficient, and increasingly accurate.
How is AI being used in drug discovery?
AI can accelerate drug discovery by harnessing the power of machine learning algorithms to analyze vast datasets of biological and chemical information, making the drug development process more efficient and cost-effective. One unique way AI does this is through the identification of potential drug candidates from unconventional sources. For example, AI can analyze data from traditional medicine systems, such as Ayurveda or Traditional Chinese Medicine, to discover novel compounds with therapeutic potential that might have been overlooked by traditional drug discovery methods.
Artificial intelligence, including machine learning and deep learning algorithms, is being applied to various stages of drug discovery:
- Target Identification: AI analyzes vast datasets to identify potential drug targets, such as proteins or genes associated with diseases. Companies like BenevolentAI have successfully used AI to uncover promising targets for conditions like neurodegenerative diseases and cancer.
- Drug Design: AI-powered algorithms assist in designing novel drug compounds. Atomwise, for example, employs deep learning to generate potential drug candidates by simulating molecular interactions.
- High-Throughput Screening: Robotics and AI-driven systems enable the rapid screening of compounds for their potential as drugs. Companies like Insilico Medicine and Recursion Pharmaceuticals employ AI to analyze screening data, making the process more efficient.
- Clinical Trial Optimization: AI can predict patient responses and optimize trial designs, reducing costs and expediting the development process. Tempus and Deep 6 are among those enhancing clinical trials with AI.
- Drug Repurposing: AI is used to find new uses for existing drugs. Biovista, for instance, repositions drugs to treat conditions they were not initially designed for, thereby saving time and resources.
What are the advantages of using AI in drug discovery?
The integration of AI in drug discovery offers numerous advantages:
- Accelerated Research: AI accelerates the identification and development of new drugs, saving years in the process.
- Cost Reduction: By optimizing processes and improving the chances of success, AI minimizes research and development costs.
- Data-Driven Insights: AI helps researchers uncover insights from massive datasets, leading to better-informed decisions.
- Personalized Medicine: AI enables the development of personalized treatment plans, tailoring medications to individual patients.
- Drug Repurposing: AI breathes new life into existing drugs, potentially unlocking treatments for previously incurable diseases.
- Enhanced Drug Safety: AI enhances drug safety by identifying potential adverse effects earlier in development.
What are the challenges of using AI in drug discovery?
AI can make drug discovery faster, more efficient, and less costly. However, there are several challenges to using AI in drug discovery, including:
- Data quality: Accurate predictions generated by AI algorithms depend on the quality of the data they utilize. When the data is lacking, inconsistent, or biased, the algorithms may struggle to produce precise predictions.
- Complex human biology: Human biology is context-dependent, and data can be hard to attain.
- Small data sets: Pharma data sets are usually smaller with fewer patients and fewer observations per patient.
- Dissemination of false information: AI models trained on incomplete or incorrect data can contribute to the dissemination of inaccurate information.
- Research gaps: Research gaps hinder the use of AI in drug discovery.
- Obstacles to data access and sharing: Obstacles to data access and sharing hinder the use of AI in drug discovery.
- Human capital challenges: Human capital challenges hinder the use of AI in drug discovery.
Regulatory uncertainty: Regulatory uncertainty hinders the use of AI in drug discovery.
How does AI impact the ethical considerations in drug discovery?
AI has the potential to impact ethical considerations in drug discovery in several ways. For example, AI could be used to make decisions about which drugs to develop, which clinical trials to conduct, and how to market and distribute drugs. This raises concerns about the potential for AI to be used to discriminate against certain groups of people or to prioritize the interests of drug companies over the health of patients.
Another ethical consideration is the potential for AI to be used to create new forms of intellectual property. For example, AI could be used to design new drugs or to develop new methods of drug delivery. This raises concerns about the potential for AI to be used to create monopolies in the pharmaceutical industry or to prevent access to new drugs for people who need them.
Finally, AI could be used to collect and analyze data about patients’ health. This raises concerns about the potential for AI to be used to invade patients’ privacy or to be used to make decisions about patient’s care without their knowledge or consent.
It is important to consider these ethical concerns as AI is increasingly used in drug discovery. We want AI to be used in a way that benefits society and does not harm individuals.
Is there any AI-generated drug already in clinical trials in human patients?
Yes, there are AI-generated drugs that have already entered clinical trials in human patients. For instance, the first drug fully generated by artificial intelligence, INS018_055, entered clinical trials with human patients in 2021. This drug was created by Hong Kong-based biotech startup Insilico Medicine. INS018_055 is the first drug with both an AI-discovered target and an AI-generated design. As of 2023, Insilico Medicine’s AI-generated drug has entered Phase II trials.
Another AI-generated drug molecule, created by British start-up Exscientia and Japanese pharmaceutical firm Sumitomo Dainippon Pharma, is being used to treat patients who have obsessive-compulsive disorder (OCD).
21 Companies Harnessing Artificial Intelligence to Accelerate Drug Discovery
The journey of AI in drug discovery has only just begun. As technology advances, we can expect more innovative breakthroughs in pharmaceutical research, offering hope for countless patients and pushing the boundaries of what is possible in the world of medicine.
These 21 companies and many others are at the forefront of this exciting revolution.
Aria Pharmaceuticals is a preclinical-stage pharmaceutical company that is revolutionizing the field of drug discovery. With a mission to improve the lives of patients facing complex, hard-to-treat diseases, Aria Pharmaceuticals is not reliant on traditional discovery methods. Instead, they have redefined the drug discovery approach by mitigating risks throughout the drug development process.
Their proprietary artificial intelligence platform, Symphony™, decodes complex biology problems in an unprecedented manner. This technology integrates and simultaneously analyzes unrelated heterogeneous data in one process, providing a holistic view of the biology and detecting signals others might miss. This innovative approach has shown promise across a diverse range of therapeutic areas with the potential to address over 1,000 diseases.
Atomwise is a preclinical pharmaceutical company that is transforming the landscape of drug discovery with its innovative use of artificial intelligence. The company has pioneered the application of deep learning for structure-based drug design, developing a machine learning-based discovery engine that combines the power of convolutional neural networks with extensive chemical libraries.
This groundbreaking approach enables Atomwise to design new molecules for the most challenging targets, helping their partners deliver better medicines more quickly. With a focus on small molecule drug discovery, Atomwise is committed to advancing its mission of making better medicines faster.
BenevolentAI is a clinical-stage, AI-enabled drug discovery and development company that is leading the way in the application of advanced AI to accelerate biopharma drug discovery. The company offers end-to-end drug discovery services, with a focus on progressing their most advanced high-potential clinical and preclinical assets.
Their lead asset, BEN-8744, for the treatment of ulcerative colitis, is currently in a Phase I clinical study. BenevolentAI’s customizable SaaS products enable scientists to make higher-confidence decisions and improve discovery and research productivity. The company is also known for its strategic collaborations with industry giants such as AstraZeneca and Merck, further validating their drug discovery offerings.
BPGbio is a clinical-stage biopharma company that is redefining the drug discovery process. Leveraging the power of artificial intelligence, BPGbio is transforming how patient biology can be modeled to accelerate and de-risk the drug discovery process.
The company’s unique approach involves the use of unbiased AI algorithms to identify, test, and validate drug targets with greater speed and precision than traditional methods. With a focus on oncology, neurology, and rare diseases, BPGbio has a robust pipeline of AI-developed therapeutics, including several in late-stage development. The company’s pioneering work is paving the way for more effective treatments for humanity.
Deep Genomics is a trailblazing biotechnology company that leverages the power of artificial intelligence to revolutionize genetic medicine. Their pioneering work in the field of AI-driven genomic analysis and drug discovery has positioned them at the forefront of personalized medicine.
Deep Genomics’ proprietary AI platform is designed to predict the molecular effects of genetic variation, enabling the rapid discovery and development of new therapies for genetic disorders. Their commitment to innovation and excellence has made them a leader in the application of AI to precision medicine, with a robust pipeline of AI-developed therapeutics that hold promise for countless patients worldwide.
Envisagenics is a trailblazer in the biotechnology industry, leveraging the power of artificial intelligence to revolutionize genetic research. The company’s primary technology, the SpliceCore® discovery platform, utilizes machine learning to identify, test, and validate drug targets with unprecedented speed and precision. This innovative approach allows Envisagenics to uncover novel RNA splicing events that can lead to cancer and other genetic diseases.
Envisagenics has also made significant strides in securing funding and forming strategic partnerships. The company has successfully raised capital from investors, won several prestigious artificial intelligence competitions, and established multiple research collaboration partnerships within the biopharma industry.
Evaxion Biotech is a clinical-stage biotech company that is pioneering the development of artificial intelligence-powered immunotherapies. With its proprietary and scalable technologies, Evaxion is decoding the human immune system to develop novel immunotherapies for cancer, bacterial diseases, and viral infections.
The company’s flagship product, EVX-01, is a peptide-based neoantigen cancer therapy intended for the first-line treatment of a variety of metastatic and unresectable melanoma. In addition to EVX-01, Evaxion has a robust pipeline of products in various stages of development, including EVX-02 and EVX-03 for cancer treatment, and EVX-B1, EVX-B2, and EVX-V1 for bacterial and viral diseases.
Exscientia is a leading player in the field of artificial intelligence-driven pharmaceutical technology. The company is committed to discovering, designing, and developing drugs using a unique AI process that includes Precision Target, Precision Design, Precision Experiment, and Precision Medicine.
Exscientia’s innovative approach allows it to automate drug design, surpassing conventional human endeavor. The company’s AI-driven systems actively learn best practice from vast repositories of discovery data, placing it at the forefront of small molecule drug discovery.
The company has a strong track record of securing funding and has attracted investors including the Bill & Melinda Gates Foundation. Exscientia’s financials are consolidated and reported in pounds sterling, reflecting its origins in Oxford, United Kingdom.
Genesis Therapeutics is a biotechnology company that is transforming clinical outcomes for patients through its proprietary molecular AI technology. The company develops small-molecule drugs to treat patients suffering from severe and debilitating diseases.
The team at Genesis Therapeutics is led by co-founder Ben Sklaroff, an early employee and former director of software at Markforged. The company prides itself on its collaboration between drug hunters, who have discovered and/or developed multiple FDA-approved drugs, and accomplished AI and software engineers.
Insitro is a data-driven drug discovery and development company that is revolutionizing the biotechnology industry. The company’s approach to drug discovery and development is unique, integrating machine learning and high-throughput biology to develop therapeutics.
Insitro’s mission is to improve the drug discovery process by predicting better and earlier which paths are more likely to lead to successful medicines, thereby avoiding many of the dead ends that often occur in pharmaceutical R&D.
Insilico Medicine is a globally recognized biotechnology company that is revolutionizing the field of drug discovery with its cutting-edge artificial intelligence technology. Based in Pak Shek Kok, Hong Kong, and New York, Insilico Medicine combines genomics, big data analysis, and deep learning to expedite in silico drug discovery.
The company’s mission is to extend healthy productive longevity by transforming drug discovery and development with generative artificial intelligence. This approach significantly reduces the time and cost to bring life-saving medications to patients. Insilico Medicine’s integrated and experimentally-validated platform enables multi-omics target discovery and deep biology analysis, considerably reducing the required time for these processes.
Lantern Pharma is a clinical-stage pharmaceutical company that is revolutionizing the field of precision cancer drugs. The company leverages artificial intelligence, machine learning, and genomic data to streamline the drug development process. Lantern Pharma’s innovative approach includes the development of new classes of precision cancer drugs with novel mechanisms of action.
The company’s AI platform, known as RADR®, includes more than 25 billion data points and uses big data analytics and machine learning to rapidly uncover biologically relevant genomic signatures correlated to drug response. This allows Lantern Pharma to identify the cancer patients that may benefit most from their compounds.
Lantern Pharma’s current portfolio consists of four drug candidates and an ADC program across eleven disclosed tumor targets, including two Phase 2 programs and several additional Phase 1 clinical trials anticipated for 2023.
Owkin is a medical company that develops a federated learning AI platform to assist pharmaceutical companies in discovering new drugs. Owkin’s unique approach integrates complex biology through AI to identify new treatments, de-risk and accelerate clinical trials, and build diagnostic tools to reduce time to impact for patients.
The company has a global reach with locations in Boston, New York, London, Paris, Nantes, and Geneva. Owkin has also formed strategic deals with top biopharma companies like Sanofi and BMS for AI drug discovery and development.
PrecisionLife is a pioneering techbio company that is transforming the understanding of complex diseases. The company, formerly known as RowAnalytics, delivers a new approach to complex disease analysis based on patients’ genomic and clinical data. It develops an AI-enabled multi-omic analysis platform to screen genomic, phenotypic, and patient health datasets, providing insights into the signatures driving complex diseases.
The company’s AI-led Innovation Engine, powered by its unique combinatorial analytics, stratifies patient populations at the highest resolution, finding all the mechanistic drivers of disease for subgroups of patients. With these insights, PrecisionLife is discovering novel drug targets and leads for unmet medical needs, identifying drug repositioning candidates for patient subgroups, enriching clinical trials and rescuing shelved programs, designing more accurate diagnostic and clinical decision support tools, and predicting and preventing chronic disease in patients.
Recursion Pharmaceuticals is a clinical-stage TechBio company that is leading the field by decoding biology to industrialize drug discovery. The company’s mission is enabled by the Recursion OS, a platform built across diverse technologies that continuously expands one of the world’s largest proprietary biological and chemical datasets.
Recursion Pharmaceuticals leverages sophisticated machine-learning algorithms to distill from its dataset a collection of trillions of searchable relationships across biology and chemistry unconstrained by human bias. By commanding massive experimental scale — up to millions of wet lab experiments weekly — and massive computational scale — owning and operating one of the most powerful supercomputers in the world, Recursion is uniting technology, biology, and chemistry to advance the future of medicine.
Relay Therapeutics is a clinical-stage precision medicine company that is transforming the drug discovery process. The company sits at the intersection of computational and experimental technologies, focusing on making small molecule medicines against precision medicine targets. The objective of Relay Therapeutics is to make the discovery of medicines both more efficient and effective.
The company’s platform detects and characterizes interactions that occur anywhere on a protein, combining computational methods with experimental approaches across the fields of structural biology. This unique approach allows Relay Therapeutics to transform the drug discovery process with the goal of bringing life-changing therapies to patients.
Schrödinger is an international scientific software company that specializes in developing computational tools and software for drug discovery and materials science. The company’s software is used by pharmaceutical companies, biotech firms, and academic researchers to simulate and model the behavior of molecules at the atomic level.
Schrödinger’s mission is to improve human health and quality of life by transforming the way therapeutics and materials are discovered. With steadfast investment in R&D, the company continues to develop and refine its scientific platform. This platform is deployed by users worldwide to enable the discovery of novel therapeutics and materials more rapidly, at a lower cost, and with a higher likelihood of success.
Simulations Plus is a leading developer of modeling and simulation software for drug discovery and development. The company’s software allows pharmaceutical scientists to predict certain key potential endpoints and dynamics, in silico, thereby reducing research & development costs and helping clients make better project decisions sooner.
The company’s products include GastroPlus, ADMET Predictor, MedChem Studio, DDDPlus, MedChem Designer, and MembranePlus. These tools are used to predict properties of molecules utilizing both artificial intelligence (AI) and machine-based technology.
Tempus is a technology company that is revolutionizing precision medicine through the practical application of artificial intelligence in healthcare. The company’s mission is to bring the power of data and artificial intelligence to healthcare, making it possible for physicians to make more informed treatment decisions.
Tempus has one of the world’s largest libraries of clinical and molecular data, along with an operating system to make that data accessible and useful. The company’s main source of revenue comes from sequencing the genome of cancer patients’ tumors, which helps doctors decide which treatments would be most effective.
Valo Health is a biotech company using data analysis and artificial intelligence to aid in drug discovery and development. Valo Health’s platform, known as the Opal Computational Platform™, combines machine learning, tissue biology, and patient data to create a suite of powerful capabilities that bring the future of drug discovery and development to bear.
The company has assembled a team of software engineers, data scientists, biologists, medicinal chemists, and big-picture thinkers to form a new kind of company. This team is dedicated to advancing the combined power of technology and patient data.
Verge Genomics is a biopharmaceutical company that is revolutionizing the treatment of neurodegenerative diseases through the use of systems biology. The company’s platform uses patient genomes, gene expression, and epigenomics to identify new therapeutic gene targets and predict effective drugs.
Verge Genomics is focused on developing therapeutics for complex diseases with high unmet need, using human genomics from patient disease tissues and machine learning. The company has created a proprietary all-in-human CONVERGE™ platform, featuring one of the field’s largest and most comprehensive databases of multi-omic patient data.
Artificial Intelligence is a game-changer in the pharmaceutical industry, with a remarkable potential to reshape drug discovery and development. As AI-powered tools become more sophisticated, we can anticipate even more remarkable discoveries and groundbreaking treatments on the horizon.