4 AI-Powered Drug Discovery Stocks to Watch as AI Reshapes Pharma

Artificial intelligence (AI) is poised to reshape pharmaceutical research by addressing some of the industry's most persistent challenges: lengthy timelines, high development costs and substantial clinical failure rates. Traditional drug discovery is largely hypothesis-driven and requires years of sequential experimentation before a viable candidate emerges. It is a common industry understanding that most drug candidates fail during clinical development. Drug development remains a lengthy and costly process, with McKinsey citing Tufts researchers’ estimate of about 10 years and $1.4 billion in out-of-pocket costs to bring a single drug to market.

AI aims to change this paradigm by allowing researchers to analyze vast biological and chemical datasets before investing heavily in laboratory testing. AI models can help identify promising targets, design drug candidates and predict biological responses, potentially making drug discovery faster and more efficient. Data from laboratory experiments can then be fed back into the models to improve future predictions, while platform licensing, partnerships and milestone payments offer additional revenue opportunities.

Against this backdrop, Recursion Pharmaceuticals RXRX,Schrödinger SDGR, Relay Therapeutics RLAY and Absci ABSI stand out for applying computational and AI-based technologies to drug discovery while advancing proprietary or partnered clinical pipelines. Although their approaches differ — from Recursion's AI-native biology platform and Schrödinger's physics-based molecular modeling to Relay's protein-motion technology and Absci's generative antibody design — they share a common objective to use computation and data to improve the efficiency and precision of therapeutic discovery.

Together, these companies offer investors exposure to the potential transformation of drug discovery, with their proprietary AI platforms, advancing clinical pipelines and partnership opportunities providing multiple avenues for long-term value creation. All four companies currently carry a Zacks Rank #3 (Hold). You can see the complete list of today’s Zacks #1 Rank (Strong Buy) stocks here.

Recursion Pharmaceuticals

Recursion's Recursion Operating System combines large-scale biological and chemical datasets, machine learning, automated experimentation and computational tools to map and navigate trillions of biological and chemical relationships. Its latest AI agents extend the platform across target discovery, drug design and clinical strategy, with the company reporting faster analysis and improved enrollment rates in supported workflows.

RXRX shares have plunged 22.8% year to date against the industry’s 4.8% growth.

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The platform's most advanced internal asset is REC-4881, an allosteric MEK1/2 inhibitor currently undergoing mid-stage development for familial adenomatous polyposis. In the phase II study, data have shown meaningful reductions in polyp burden, prompting discussions with the FDA on a potential registrational pathway. Additional phase II safety and efficacy data are expected to be presented at a medical conference in November.

Beyond REC-4881, Recursion's clinical pipeline includes several early-stage candidates, including REC-1245 for biomarker-enriched solid tumors and lymphoma, REC-617 for advanced solid tumors, REC-3565 for B-cell malignancies and REC-4539 for solid tumors and hematologic cancers. Pipeline momentum is also broadening. REC-7735, an AI-designed PI3Kα H1047R inhibitor, has received investigational new drug (IND) application clearance and is expected to enter a phase I/II study in the second half of 2026 for selected PIK3CA H1047R-mutant solid tumors.

Schrödinger

Schrödinger operates a physics-based computational platform that integrates molecular simulation with machine learning to discover and optimize novel molecules. Its newly launched Bunsen agentic AI co-scientist combines AI with physics-based simulation to help researchers execute molecular discovery workflows, while its predictive toxicology initiative seeks to reduce development-failure risk.

SDGR shares have lost 1.6% year to date against the industry’s 2.9% growth.

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Schrödinger’s lead proprietary pipeline consists of SGR-1505, a MALT1 inhibitor in phase I for relapsed/refractory B-cell malignancies, and SGR-3515, a Wee1/Myt1 inhibitor undergoing phase I development for advanced solid tumors. Both programs were discovered using Schrödinger's computational capabilities, with SGR-3515 showing preliminary clinical activity and SGR-1505 demonstrating encouraging activity in B-cell malignancies in earlier updates.

Importantly, Schrödinger is taking a more capital-efficient approach to clinical development. The company plans to complete its ongoing early-stage studies while seeking strategic partners to advance SGR-1505 and SGR-3515 beyond phase I rather than independently funding additional studies. This model allows Schrödinger to monetize its computational platform through software and collaborations while retaining potential upside from proprietary therapeutics.

Relay Therapeutics

Relay Therapeutics’ Dynamo platform combines computational and experimental approaches centered on protein motion to identify small-molecule therapies against previously difficult targets. The platform is focused on precision oncology and genetic diseases, with the company's strategy built around linking target biology with patient selection.

RLAY shares have soared 134.8% year to date against the industry’s 2.1% decline.

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The centerpiece is zovegalisib (RLY-2608), a mutant-selective PI3Kα inhibitor, currently being evaluated in the phase III ReDiscover-2 study, in combination with fulvestrant in previously CDK4/6-treated, PIK3CA-mutated HR+/HER2- advanced breast cancer. RLAY also plans to initiate a separate late-stage frontline breast cancer study of the candidate, subject to regulatory feedback, while the phase I/II ReInspire study is evaluating zovegalisib in PIK3CA-driven vascular anomalies.

Relay Therapeutics is also expanding beyond PI3Kα with RLY-8161, an NRAS-selective inhibitor being studied in a phase I/II study for NRAS-mutant melanoma and other NRAS-mutant solid tumors. In addition, the company is advancing a non-inhibitory chaperone program for Fabry disease and earlier discovery programs, giving investors exposure to multiple applications of its computational platform.

Absci

Absci uses its Integrated Drug Creation platform, which combines generative AI models, synthetic biology and rapid laboratory validation. Its Origin-1 generative design model and lab-in-the-loop system are intended to accelerate antibody discovery by continuously feeding experimental results back into the computational models. The company previously said it advanced its first two programs from AI design to IND in about two years for roughly $15 million per program compared to an industry average of four to six years at a cost exceeding $50 million.

ABSI shares have skyrocketed 163% year to date compared with the industry’s 4.8% growth.

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The key asset is ABS-201, an AI-designed anti-prolactin receptor antibody being evaluated in the phase I/IIa HEADLINE study for androgenetic alopecia or pattern hair loss. In June, Absci reported favorable interim early-stage safety data and an estimated half-life of at least 65 days, supporting the candidate’s targeted dosing interval of two or three injections over six months. The company expects interim proof-of-concept data in the second half of 2026 and full proof-of-concept data in early 2027.

Absci is also preparing to broaden ABS-201 into endometriosis, with a phase II study initiation targeted for the fourth quarter of 2026 and potential proof-of-concept data in the second half of 2027. Meanwhile, ABS-202, another AI-designed anti-PRLR antibody, remains in preclinical development for an undisclosed immunology and inflammation indication. The company's strengthened balance sheet, including a $40 million strategic investment from Eli Lilly, is expected to fund operations into the second half of 2028, providing additional runway for these milestones.

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