AI has proven to be a vital tool in accelerating and improving the speed at which cures and vaccinations are discovered, as the COVID-19 pandemic has shown. Since then, AI has helped the biopharma industry achieve a number of breakthroughs in drug discovery. These include the swift and effective discovery of a new antibiotic called abaucin to fight bacteria that is resistant to multiple drugs, as well as the complete discovery and design of a drug that is currently undergoing clinical trials.
These five AI drug discovery firms are presently using their technology to make impressive advancements.
Atomwise
Atomwise is attempting to transform small molecule medication discovery by utilizing artificial intelligence. In order to give medication developers more chances to hit the mark, the company aims to simplify the drug development process and take on the most difficult, seemingly unachievable tasks.
With Atomwise’s method, the process of finding new drugs becomes more logical, successful, and efficient by moving away from chance discovery and toward search based on structure. Deep learning for structure-based medication design is integrated into the company’s AtomNet platform, which allows for quick, AI-powered searches of its own library of more than three trillion synthesizable molecules.
One of Atomwise’s largest agreements was a strategic multi-target research relationship with pharmaceutical behemoth Sanofi. Through this partnership, Atomwise will use Sanofi’s AtomNet platform to computationally uncover and investigate up to five therapeutic targets.
The business also recently declared the nomination of its first AI-driven development candidate, an allosteric TYK2 inhibitor that is orally bioavailable. A crucial mediator in cytokine signaling pathways connected to a variety of immune-mediated inflammatory diseases, TYK2 plays a pivotal role. The candidate may be able to treat a variety of autoimmune and autoinflammatory conditions by modifying the TYK2 pathway. These conditions include psoriasis, psoriatic arthritis, systemic lupus erythematosus, and inflammatory bowel illness. Now, Atomwise plans to submit an IND in the second half of 2024.
Cradle
Using generative AI, the Dutch firm Cradle helps biologists design better proteins and speeds up research and development, making it simpler, faster, and more affordable to produce bio-based products for the health of people and the earth. The company uses data from Cradle’s own wet lab and billions of protein sequences to train its AI algorithms.
In the last year, the company has already brought on nine top industry partners, such as Twist Bioscience, Novozymes, and Janssen Research & Development. Currently, it is engaged in over 12 research and development projects aimed at engineering various protein modalities, such as peptides, antibodies, enzymes, and vaccines, covering a wide range of desired protein properties, including binding affinity, specificity, stability, and activity.
Cradle secured $24 million in series A funding in November 2023, with Kindred Capital and Index Ventures serving as lead investors. The AI drug discovery startup has raised $33 million in total as of this fundraising round.
Exscientia
Exscientia, a precision medicine firm driven by artificial intelligence, is regarded as a pioneer in the biopharma industry. The company’s mission is to use AI technology to identify, design, and manufacture the greatest treatments possible as quickly and effectively as feasible. In order to successfully guide treatment selection, enhance patient outcomes in a prospective interventional clinical study, and advance AI-designed small molecules into the clinical setting, the business created the first-ever functional precision oncology platform.
The most advanced candidate from Exscientia, GTAEXS617, is being investigated for the treatment of advanced solid tumors, such as breast, non-small cell lung, head and neck, and other malignancies, in a phase 1/2 trial known as ELUCIDATE.
The AI drug discovery startup has partnered with other companies, including notable agreements with Merck and Sanofi. In 2017, Exscientia and Sanofi signed a $273 million licensing agreement that centered on the development of bispecific small molecule medications for metabolic illnesses. This marked the beginning of the two firms’ collaboration. In 2022, Exscientia and Sanofi reached a research and license deal to explore up to 15 potential small molecule candidates in the fields of immunology and oncology. Recently, however, Exscientia and Merck announced a new $674 million agreement centered on the discovery of innovative small molecule therapeutic candidates in the fields of immunology, neuroinflammation, and oncology.
Iktos
Iktos, a Paris-based company, uses artificial intelligence (AI) technology for medication design and discovery. It does this by quickly identifying tiny compounds with potential for clinical usage. Iktos wants to increase the likelihood that drug candidates will successfully advance to clinical development while also expediting the drug discovery process through the use of AI. Through more than 50 academic and industrial partnerships with pharmaceutical and biotech companies including Janssen, Merck, Pfizer, Servier, Ono, and Teijin, Iktos has already verified this strategy.
The company offers four main products that help small molecule drug discovery become more productive. These are: Makya, a ligand and structure-based de novo drug design platform; DockAI, which improves efficiency by combining docking with a cutting-edge active learning methodology; Spaya, a synthesis planning software; and Spaya API, a high throughput synthetic accessibility scoring tool for virtual molecule libraries.
The company said in March 2023 that it had closed a €15.5 million ($16.4 million) series A financing round. This allowed the company to expand its SaaS software offering, enhance its AI and drug discovery capabilities, and introduce Iktos Robotics, an end-to-end drug discovery platform that uses chemical synthesis automation and AI to significantly speed up drug discovery timelines.
Insilico Medicine
Insilico Medicine wants to drastically cut the time and expense involved in getting life-saving medications to patients by applying AI to every stage of pharmaceutical research and development. The business uses next-generation AI systems to link biology, chemistry, and clinical trial analysis in order to do this. Its fully-integrated drug discovery package, Pharma.AI, includes InClinico (which designs and predicts clinical trials), Chemistry42 (which generates novel compounds), and PandaOmics (which finds and prioritizes novel targets).
An key milestone for the industry was reached in June 2023 when Insilico’s drug candidate, INS018_055, for the treatment of idiopathic pulmonary fibrosis, became the first fully AI-discovered and AI-designed medication to enter a phase 2 clinical trial. Two more medications developed by the AI company are in the clinical phases and were partly inspired by AI. There are two: one for solid tumors and the other for COVID-19.
It’s also important to note that Insilico and Sanofi inked a significant collaboration agreement in November 2022 that may potentially be worth $1.2 billion. According to the deal, Sanofi would use Pharma.AI from Insilico to find disease targets, produce fresh molecular data, and forecast clinical trial outcomes in order to promote therapeutic candidates for a maximum of six new targets.
AI in medicine discovery: Businesses prosper as demand soars
Grand View Research estimates that the global market for artificial intelligence (AI) in drug discovery was worth $1.1 billion in 2022 and will rise at a compound annual growth rate (CAGR) of 29.6% between 2023 and 2030. According to the research, the need for AI-enabled solutions in the drug discovery processes is being driven by the life science industry’s growing production capacity as well as the growing demand for the discovery and development of novel medical therapies.
AI for drug discovery is undoubtedly a developing subject in the biopharma business, as this report indicates. More businesses will inevitably enter the field as it expands in an effort to transform drug discovery and the biopharma sector overall in order to make the process of developing new drugs faster, more reliable, more accurate, and more scalable.
