20 Top AI Drug Discovery Companies and Startups to Watch in 2026

Executive Summary: Which are the Top 20 AI Drug Discovery Companies to Watch?

1. Karyon Bio (USA) provides an AI-driven platform for medication discovery and diagnostics.
2. Theremia (France) creates an AI-powered platform that optimizes medication derivatives.
3. Ternary Therapeutics (UK) offers an AI-powered platform that creates molecular glue treatments for protein targets.
4. Deep MedChem (Czech Republic) develops AI-powered platforms with virtual high-throughput screening and molecular modeling.
5. Expert Systems (USA) builds a human-AI hybrid platform that accelerates the preclinical drug discovery process.
6. PURR.AI (Portugal) offers an AI platform that analyzes intricate biological data from various modalities to find new drug targets.
7. SYDRA (Switzerland) provides a platform that combines cheminformatics, machine learning, and systems biology to find synthetic chemicals.
8. Atomistic Insights (USA) develops a deep learning platform that incorporates physics-based modeling to forecast protein dynamics.
9. Synaptiflora (Israel) creates an AI-powered platform that advances microbiome-based drug development.
10. ProPhet (Israel) builds an AI-powered platform for small molecule drug development.
11. LinkGevity (UK) advances longevity science-led drug discovery.
12. Examol (USA) enables AI-led computational drug discovery.
13. Helical (Luxembourg) develops a bio-foundation models platform.
14. DenovAI Biotech (Israel) offers an AI-driven de novo therapeutic protein design platform.
15. Orakl Oncology (France) uses precision medicine to speed up the development of cancer drugs.
16. AVAYL (Germany) enables medical information-based response matching.
17. Aevai Health (Netherlands) offers an AI-powered chatbot to streamline participant engagement and data collection for biobanks.
18. 9Bio Therapeutics (Canada) builds an AI-guided structural biology platform.
19. chAIron (Switzerland) provides AI-driven molecules analysis.
20. Aureka Biotechnologies (USA) makes an AI-driven generative therapeutic design platform.

Global Startup Heat Map highlights Emerging 20 AI Drug Discovery Startups to Watch

Through the Big Data & Artificial Intelligence (AI)-powered StartUs Insights Discovery Platform, covering over 7M+ startups, 20K+ technology trends, plus 150M+ patents, news articles & market reports, we identified 20 AI drug discovery startups.

The Global Startup Heat Map below highlights emerging AI drug discovery startups you should watch in 2026, as well as the geo-distribution of 350 startups & scaleups we analyzed for this research.

According to our data, we observe high startup activity in the US and India, followed by the UK. The top 5 Startup Hubs for AI Drug Discovery are San Francisco, London, Cambridge, Boston, and New York City.

Meet Emerging AI Drug Discovery Startups to Watch in 2026

We hand-picked startups to showcase in this report by filtering for their technology, founding year, location, funding, and other metrics. These AI drug discovery startups work on solutions ranging from computational discovery and bio-foundation models to therapeutic protein and molecule analysis.

1. Karyon Bio

• Founding Year: 2024
• Location: Mountain View, California, USA
• Use For: Medication Discovery and Diagnostics

US-based startup Karyon Bio offers an AI-driven platform for medication discovery and diagnostics for metabolic dysfunction-associated liver disease (MALD) and metabolic
dysfunction–associated steatohepatitis (MASH).

The platform combines machine learning models, transcriptomic data, and molecular biology to find predictive biomarkers and accelerate focused treatment development. It analyzes multi-omics information to identify disease-specific pathways and categorize patient subgroups according to treatment response and disease progression.

This technology reduces the time needed for preclinical validation and enhances early-stage drug target identification by fusing AI-driven insights with biological information. The platform also provides precision diagnostics for individualized treatment plans. It reduces the time needed for drug discovery and improves diagnostic precision.

2. Theremia

• Founding Year: 2023
• Location: Paris, France
• Use For: AI-driven Drug Efficacy Platform

French startup Theremia creates an AI-powered platform that optimizes medication derivatives for certain population subgroups, primarily neurological illnesses. The platform utilizes clinical, molecular, and demographic datasets to analyze therapy responses in patient profiles.

It enables customization of molecules for particular phenotypic or genetic characteristics. The platform also utilizes machine learning to forecast the effectiveness and adverse effect profiles of different medication candidates. This lowers the possibility of negative reactions.

3. Ternary Therapeutics

• Founding Year: 2024
• Location: London, United Kingdom
• Use For: Molecular Glue Therapeutics Designing

UK-based startup Ternary Therapeutics creates TernaryTx, an AI-powered platform that creates molecular glue treatments for protein targets. The platform analyzes structural biology data and networks of protein-protein interactions to find new binding interfaces that promote targeted protein breakdown.

TernaryTx simulates molecular docking and optimizes glue candidates for stability, specificity, and efficacy using machine learning techniques. For this, it uses the ubiquitin-proteasome system based on structural insights and high-throughput screening data.

It also uses precision molecular glue design to expand the druggable proteome. Additionally, it uncovers novel mechanisms of action for complicated illnesses, particularly in immunology.

4. Deep MedChem

• Founding Year: 2023
• Location: Prague, Czech Republic
• Use For: Medicinal & Computational Chemists AI Discovery

Czech startup Deep MedChem creates CHEESE, an AI-powered platform. It speeds up drug development by using virtual high-throughput screening and molecular modeling. CHEESE‘s search engine allows chemists to quickly find potential drug-like compounds by comparing various chemicals based on their 3D shapes and electrostatic properties.

Its modeller facilitates quick training and deployment of property prediction models, while the electrostatics module provides near-DFT accuracy for electrostatic potential estimations at much faster speeds.

Additionally, CHEESE‘s explorer module offers an interactive, real-time representation of molecular similarities across extremely broad chemical areas in unexplored areas.

This way, the platform provides researchers with high-performance, scalable tools for lead identification, optimization, and molecular property prediction. Deep MedChem integrates AI with domain-specific chemical operations to expedite early-stage drug discovery.

5. Expert Systems

• Founding Year: 2023
• Location: San Diego, California, USA
• Use For: AI-enabled Drug Discovery Solutions

US-based startup Expert Systems creates a human-AI hybrid platform that accelerates the preclinical drug discovery process, from early clinical development to target identification.

The platform performs virtual screening, forecasts pharmacological profiles, evaluates toxicity, and assesses chemical liabilities in drug candidates. It combines algorithms with public and proprietary databases to provide detailed insights for informed decision-making.

Additionally, it maps candidate compounds against disease-relevant targets using cheminformatics, bioinformatics, and clinical informatics. It also analyzes the intellectual property landscape to reduce legal and commercial risk. The platform facilitates data-driven candidate prioritization and expedites the transition from in silico modeling to first-time-in-man research.

6. PURR.AI

• Founding Year: 2023
• Location: Coimbra, Portugal
• Use For: Novel Drug Targets

Portuguese startup PURR.AI offers an AI platform that analyzes intricate biological data from various modalities to find new drug targets. It focuses on age-related neurological diseases.

The startup’s modular AGELESS suite benefits from multiple biological data modalities to identify new therapeutic targets, integrate biomedical knowledge, and generate reliable predictions for neurodegeneration research.

AGELESS.DB serves as an advanced database for aggregating insights from diverse public and proprietary sources to support real-time, domain-specific AI applications. AGELESS.MAP applies AI-driven analytics for intelligent mapping of biological pathways to improve understanding of disease mechanisms and enables innovative therapeutic strategies.

PURR.AI combines machine learning with transparent models to ensure responsible use of AI in critical biomedical research. This simplifies target identification and enhances predictive accuracy for researchers, biotech innovators, and clinicians. It also expands opportunities for novel drug development in aging and neurological health.

7. SYDRA

• Founding Year: 2024
• Location: Schlieren, Switzerland
• Use For: Synthetic Drug Algorithms

Swiss startup SYDRA develops SYnthetic DRug Algorithms (SYDRA), an AI-assisted platform to find and validate new geroprotectors for age-related illnesses. The platform combines cheminformatics, machine learning, and systems biology to find synthetic chemicals that alter important aging pathways and prolong healthspan.

It is subsequently evaluated for efficacy in vivo using exclusive screening models. The platform identifies drug-like compounds by analyzing biological networks and multi-omics data. SYDRA enables iterative improvement of chemical libraries and target interactions.

The platform specializes in biogerontology to focus solely on treatment mechanisms and biomarkers associated with longevity. SYDRA expedites the creation of geroprotective medications and provides efficient and scientifically supported treatments.

These treatments target the underlying causes of aging and degenerative diseases with the platform’s biological validation pipeline and algorithmic design engine.

8. Atomistic Insights

• Founding Year: 2023
• Location: Atlanta, Georgia, USA
• Use For: Protein Dynamics for Advanced Medicines

US-based startup Atomic Insights provides a deep learning platform that incorporates physics-based modeling. The platform forecasts protein dynamics and accelerates the development of advanced treatments in inflammatory diseases.

This methodology increases the targetable surface of proteins by simulating atomic-level motion to find cryptic pockets. These are temporary and obscure binding sites that may get overlooked by traditional techniques.

The platform ranks lead compounds more precisely by recording dynamic structural properties and ligand-protein interactions over time. Additionally, it integrates structural flexibility and energy landscapes into its predictive models to increase the accuracy of virtual screening.

The startup uses machine learning, structural biology, and computational chemistry to discover inaccessible drug discovery pathways. This way, the startup uses protein mobility as a key factor in therapeutic success to enhance hit-to-lead results and provide more potent medication prospects.

9. Synaptiflora

• Founding Year: 2024
• Location: Haifa, Israel
• Use For: Microbiome Insights Drug Discovery

Israeli startup Synaptiflora offers SynaptiCore, an AI-powered platform that advances microbiome-based drug development. The platform integrates microbiome composition, metabolomics, and host interactions.

It simulates host-microbiome interactions at scale to identify microbial fingerprints and metabolic pathways that impact drug response and disease development. The platform provides pharmacies with data to predict treatment success based on microbiome composition, optimize drug selection, and enhance patient stratification.

This enables customizable modeling workflows and real-time analytics. These adjust to a variety of treatment domains, from immunology to metabolic illnesses. The platform also aids in the creation of more precise and efficient treatments by connecting microbial capabilities to molecular targets.

Synaptiflora advances traditional drug discovery by using microbiome intelligence to decrease trial-and-error in early-stage research. It improves personalization and expedites the delivery of clinically relevant therapies.

10. ProPhet

• Founding Year: 2024
• Location: Rehovot, Israel
• Use For: AI-driven Small Molecule Drug Discovery

Israeli startup ProPhet creates an AI-powered platform for small molecule drug development. It focuses on structurally complex proteins that are considered undruggable using traditional techniques.

The platform leverages machine learning and computational chemistry to model protein dynamics and predict molecular interactions. This enables the quick identification of drug candidates without comprehensive structural data.

The platform utilizes physics-informed algorithms to screen large chemical libraries. It assesses binding potential and produces results that are easy to understand and rooted in scientific rigor.

As a result, the platform accelerates early-stage R&D by integrating high accuracy and prediction speed across low-visibility protein targets. ProPhet thus provides a scalable and affordable way to aid pharmaceutical companies in growing their medicinal pipelines.

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11. LinkGevity

• Founding Year: 2023
• Location: Cambridge, United Kingdom
• Solution: Tissue Damage Prevention
• Funding: Announced KQ Labs Programme Investment

LinkGevity creates Anti-Necrotics, a class of medications that prevent necrosis, a major factor in both acute wounds and chronic illnesses.

It prevents tissue damage in circumstances like acute renal injury, cardiovascular illnesses, and neurodegenerative disorders by targeting the molecular mechanisms that cause necrotic cell death.

Its constituents reduce necrosis to offer a viable substitute for organ transplantation or dialysis. LinkGevity’s method directly prevents cell death, increasing patient survival and quality of life, unlike traditional therapies that only treat symptoms.

The startup’s technology advances regenerative medicine by maintaining cellular function and slowing the progression of inflammation-driven diseases.

12. Examol

• Founding Year: 2023
• Location: Pittsburgh, Pennsylvania, United States
• Solution: Discovery of New Treatments

Examol develops a cloud-native AI-driven drug discovery platform that maximizes and expedites the discovery of new treatments. This technology enables researchers to execute virtual chemistry simulations by combining computational techniques with data infrastructure.

The platform improves drug candidate selection by enabling smooth machine-learning model execution without costly infrastructure configurations.

Examol’s AI-powered molecular modeling improves hit-to-lead optimization while reducing time and expenses associated with pharmaceutical research and development.

The platform enables scientists to enhance prediction accuracy and iterate more quickly through collaborative workflows and scalable computation.

Examol offers a potent solution for biotech companies, pharmaceutical corporations, and university researchers to create efficient treatments at a faster pace, improving accessibility to AI-driven drug discovery.

13. Helical

• Founding Year: 2023
• Location: Gare, Luxembourg
• Solution: DNA and mRNA Study

Helical creates an open-core bio foundation models platform that uses AI to study DNA and mRNA to find new drugs. The platform enables more accurate analysis of genetic sequences by providing researchers access to proprietary and open-source models.

It offers a marketplace for AI-powered biomedical applications, a data atlas, and model training tools. Helical speeds up mRNA sequence optimization, target identification, and biomarker discovery by incorporating AI-powered genome interpretation.

The startup utilizes AI-based molecular design tools and large biological information to improve drug development workflows.

It turns molecular biology into a data-driven field through automation and deep learning, improving the accuracy, scalability, and effectiveness of drug development.

Its platform benefits biotech and pharmaceutical companies to create next-generation RNA-based therapies and customized medicine.

14. DenovAI Biotech

• Founding Year: 2023
• Location: Rehovot, Israel
• Solution: Predict, Design, and Optimize Protein Structures

DenovAI Biotech offers an AI-driven de novo therapeutic protein design platform that builds protein binders and highly targeted antibodies from scratch.

The platform predicts, designs, and optimizes protein structures with high binding specificity by utilizing computational molecular biophysics and machine learning.

The startup’s method produces custom-engineered proteins more quickly compared to traditional protein discovery, which depends on screening enormous libraries. This discovery enables quicker biologics for infectious diseases, autoimmune conditions, and cancer.

DenovAI Biotech improves target selectivity, increases molecular stability and efficacy, and decreases trial-and-error in drug discovery by concentrating on rational protein design.

This technology advances biologic drug development by accelerating and improving the precision, and scalability of therapeutic innovation for pharmaceutical companies and biotech researchers.

15. Orakl Oncology

• Founding Year: 2023
• Location: Paris, France
• Solution: Development of Cancer Drugs
• Funding: Raised EUR 11 million

Orakl Oncology uses precision medicine to speed up the development of cancer drugs by collaborating with biotech and pharmaceutical companies. The startup focuses on AI-driven biomarker identification and therapeutic optimization to improve cancer patients’ treatment outcomes.

Its O-Predict forecasts patient responses to new drug candidates and predicts key clinical outcomes such as the number of responders and progression-free survival.

O-Validate generates biological evidence of causality, supporting target and biomarker validation and enabling data-based strategic decision-making across drug development stages.

Orakl Oncology improves the accurate identification of druggable targets and enhances patient stratification by combining genetic, proteomic, and real-world clinical data.

Its patented approach lowers the chance of late-stage clinical failures by predicting resistance pathways, optimizing drug combinations, and improving therapeutic efficacy evaluation.

16. AVAYL

• Founding Year: 2023
• Location: Berlin, Germany
• Solution: Medical Information Management

AVAYL develops MedPro, an AI-driven medical information management platform for life science companies. MedPro automates response matching, literature reviews, and the creation of medical content by combining AI with proprietary machine learning algorithms.

It ensures precise, high-quality, and compliant medical communication by processing large volumes of clinical trials and regulatory data. MedPro assists medical affairs teams in managing questions, delivering data-supported responses, and enhancing content accuracy by decreasing manual labor and streamlining workflows.

The platform benefits pharmaceutical, biotech, and healthcare companies due to its real-time analytics and automation features, which simplify regulatory submissions, compliance documentation, and medical research interpretation.

17. Aevai Health

• Founding Year: 2023
• Location: Amsterdam, Netherlands
• Solution: Data Collection for Biobanks
• Funding: Raised funding from Round One Ventures

Aevai Health offers Alva, an AI-powered chatbot to streamline participant engagement and data collection for biobanks and clinical research organizations.

Alva enhances the caliber and dependability of health data that is gathered by engaging in thoughtful, context-aware dialogues with study participants, patients, and donors.

The chatbot offers dynamic, real-time interaction as compared to conventional biobank data-gathering techniques that depend on static surveys and human follow-ups. This ensures that data is correct, up-to-date, and reflective of evolving patient conditions.

In addition, the chatbot has automated outcome tracking built in, which enables researchers to keep tabs on patient development and modify study procedures as necessary.

Aevai Health maximizes biobank efficiency, speeds up research results, and enables precision medicine discoveries by combining natural language processing, predictive analytics, and automated compliance tracking.

18. 9Bio Therapeutics

• Founding Year: 2023
• Location: Quebec City, Canada
• Solution: Differentiate Healthy Cells from Cancerous Ones

9Bio Therapeutics creates a structural biology platform guided by AI to create oncology treatments with higher accuracy and effectiveness. The platform ensures better targeted therapeutic treatments by using metabolomic profiling and protein structure analysis to differentiate healthy cells from cancerous ones.

The startup creates compounds with enhanced pharmacokinetics and less peripheral toxicity by concentrating on the biochemical and structural changes in diseased tissues.

Its in-house AI algorithms analyze large protein-ligand interaction databases, which enable the quick discovery of new binding sites and therapeutic targets.

9Bio Therapeutics maximizes therapeutic selectivity to enhance safety profiles while preserving efficacy without affecting healthy tissues.

This solution aids in the development of next-generation precision oncology medications by decreasing the possibility of off-target effects and increasing clinical success rates.

19. chAIron

• Founding Year: 2023
• Location: Lausanne, Switzerland
• Solution: Personalized Medicine and Drug Discovery

chAIron combines AI and human expertise to expand molecular knowledge and optimize therapeutic development for biopharmaceutical companies and research institutions.

The platform creates a thorough understanding of molecular structures and medication interactions by combining real-world data, omics insights, scientific literature, and market trends.

chAIron assists researchers in uncovering hidden relationships between molecules, illnesses, and possible treatment uses through the use of deep learning and sophisticated computational modeling.

It benefits pharmaceutical businesses to prioritize high-value assets, find new indications for current medications, and improve clinical trial tactics with this insight-driven method.

Further, the startup lowers the risks involved in early-stage medication development by offering predictive analytics to evaluate the safety and efficacy of drugs.

The platform speeds up innovation in personalized medicine and drug discovery by enhancing research and development decision-making. This ensures that promising treatments reach patients more quickly and effectively.

20. Aureka Biotechnologies

• Founding Year: 2023
• Location: Laguna Hills, California, United States
• Solution: Protein Engineering Procedures Improvement

Aureka Biotechnologies makes an AI-driven generative therapeutic design platform, integrating high-throughput autonomous evolution, functional screening, and deep learning to optimize biologic drug development.

The startup utilizes a self-learning molecular evolution method to rapidly examine millions of potential treatments.

It produces large volumes of biological data that combines AI-driven insights with automated experimental workflows to improve protein engineering procedures.

It enables researchers to quickly develop and improve therapeutic proteins due to its iterative learning cycle, which improves their stability, potency, and bioavailability.

Aureka Biotechnologies’ strategy reduces research timeframes by transforming therapeutic development into a data-driven engineering discipline, in contrast to traditional biologic discovery methods that rely on labor-intensive screening.

Its platform benefits pharmaceutical and biotech companies to create precision-engineered antibodies, protein-based therapies, and next-generation biologics.

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