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Artificial Intelligence in Drug Discovery Market to Hit USD 6.89 Billion by 2029 with 29.9% CAGR | MarketsandMarkets™

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DELRAY BEACH, Fla., Nov. 12, 2024 /PRNewswire/ — The global artificial intelligence (AI) in drug discovery market is projected to reach USD 6.89 billion by 2029 from USD 1.86 billion in 2024, at a CAGR of 29.9% from 2024  to 2029. The rising shift towards integrating AI for understanding diseases and small molecule design and optimization use cases augments the growth of the market. AI tools play a major role in accelerating target identification, optimizing lead compound selection, and predicting drug efficacy and toxicity. Supervised methods such as regression, decision trees, and neural networks help predict material properties and drug candidate profiles. In contrast, unsupervised techniques such as clustering algorithms (k-means and hierarchical clustering) and dimensionality reduction identify hidden trends, patterns, and groupings in data, aiding in novel drug discovery. Deep Learning is employed to predict molecular properties, design new compounds, and other applications. Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs) are more commonly used for handling complex data, such as sequences or molecular structures. Generative Adversarial Networks (GANs) are utilized to generate de novo or novel drug candidates, molecular structure simulation, and lead optimization. These tools help streamline processes, as well as reduce the time and cost involved in screening, optimizing, and discovering new drug candidates.

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Based on therapeutic area, the artificial intelligence (AI) in drug discovery market is segmented into oncology, infectious diseases, neurology, metabolic diseases, cardiovascular diseases, immunology, mental health, and others (respiratory diseases, nephrology, dermatological diseases, genetic disorders, inflammatory diseases, and gastrointestinal). The neurology segment held the fastest market share in the Al drug discovery market due to the increasing number of neurological disorders and the difficulties associated with drug discovery in this field, The use of Al technologies accelerates drug development because neurological diseases such as Parkinson’s, Alzheimer’s, and multiple sclerosis are difficult to diagnose and treat.

According to the WHO, in 2021, neurological conditions affected over 3 billion people worldwide. This emphasizes the need for innovative healthcare solutions. Al-powered drug discovery platforms work well in neurology, allowing faster and more accurate analysis of complex neurological data to identify potential drug candidates. The increasing availability of large datasets from clinical trials, genomics, neuroimaging, and electronic health records (EHR) records, as well as the growth investments in neurology, also contribute to market growth. In 2023, venture investments in neurology companies were USD 1.14 billion in the US. Resources like the Alzheimer’s Disease Neuroimaging Initiative (ADNI) provide vast data for machine learning applications.

Based on the process, artificial intelligence (AI) in drug discovery market is broadly classified into target identification & selection, target validation, hit identification & prioritization, hit-to-lead identification/lead generation, lead optimization, and candidate selection & validation. Hit-to-lead identification/lead generation accounts for the largest process segment in this market; it is also expected to register the highest growth owing to its critical role in streamlining the early stages of the drug development process. AI can significantly reduce the number of compounds and experiments required to find and optimize leads. This procedure uses Al algorithms to analyse large datasets, such as chemical libraries and biological interactions, to identify potential drug candidates or hits and develop them into viable leads. AI helps address long design-make-test cycles across discovery journeys. Faster screening and better exploration of vast chemical libraries are fuelling market growth for AI solutions for hit-to-lead identification/lead generation. For example, activity prediction enables more targeted experiments, and predictive analytics can help forecast compound properties. However, the lack of existing clinical data for a new molecule can hinder market growth.

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There are several opportunities in AI in drug discovery market such as growing biotech industry, emerging markets, AI in single cell experiments, Growing demand for precision medicine and personalized medicine. Key players in the artificial intelligence (AI) in drug discovery are NVIDIA Corporation (US), Exscientia (UK), Google (US), BenevolentAI (UK), Recursion (US), Insilico Medicine (US), Schrödinger, Inc. (US), Microsoft (US), Atomwise Inc. (US), Illumina, Inc. (US), Valo Health (US) among others. These players not only have a comprehensive and diverse product portfolio but also a strong geographic presence.

The key players in this market can tap these opportunities to enhance and improve their product offerings and develop innovative AI solutions for various processes, use cases, and end users. Moreover, these companies can integrate AI in drug design and optimization, understanding diseases, drug repurposing, single-cell analysis, and identification of biomarkers, disease types, and subtypes. Additionally, key players invest in AI algorithms that can examine complicated data and interpret disease mechanisms and pathways. Collaborations and partnerships between key players continue to grow rapidly, which in turn has accelerated the development of targeted therapies and contributed to rapidly expanding drug pipelines.

These market players have offered a diverse range of products and services and have operations worldwide with a major focus on North America. They rely on technological advancements to avail themselves of innovative end-to-end solutions, software, and services and increase their global footprint. These players focus on product launches and enhancements, investments, partnerships, collaborations, agreements, joint ventures, funding, acquisitions, expansions, conferences, FDA clearances, sales contracts, alliances, and other recent developments to expand their global reach and develop AI in drug discovery solutions.

NVIDIA Corporation:

NVIDIA Corporation, a prominent technology company, has made remarkable advances in artificial intelligence (AI), particularly drug discovery. NVIDIA GPUs power AI workloads in drug discovery applications such as molecular modeling, simulation, and machine learning. Nvidia’s AI software includes development tools, libraries, and frameworks that can be used to build and deploy AI applications for drug discovery. The company provides generative AI platforms like BioNeMo and Clara Discovery. NVIDIA BioNeMo simplifies the deployment of AI models, hastening the transition to AI-driven drug discovery. It offers models for 3D protein structure prediction, molecule generation, property predictions, and molecular docking. Users can customize AI models with their data, access pre-trained models, and integrate them into drug discovery workflows. NVIDIA Clara Discovery is a software suite that includes a variety of tools for AI-driven drug discovery.

NVIDIA Corporation operates more than 50 offices across the Americas, Asia, and Europe, along with manufacturing facilities in the US and Taiwan. The company collaborates with several pharmaceutical companies and biotech startups to develop solutions for AI-driven drug discovery. For example, in November 2023, NVIDIA collaborated with Genentech to improve computational models and incorporate generative AI into drug discovery processes, allowing for faster exploration of molecular designs.

Insilico Medicine:

Insilico Medicine is an end-to-end generative AI-driven biotech company accelerating drug discovery and development to treat cancer and age-related diseases. Its proprietary Pharma.AI platform spans biology, chemistry, and clinical development. The company pioneered the application of reinforcement learning and generative adversarial networks (GANs) to develop new molecular structures for diseases with known and unknown targets. Its products and services are used by pharmaceutical companies, biotechnology companies, and academic research institutions. Insilico Medicine has produced a diversified internal pipeline of 31 programs for 29 drug targets. The company’s lead drug is ISM001-055, a small-molecule chemical drug candidate primarily designed to treat fibrosis-related indications, including idiopathic pulmonary fibrosis. The company has offices in the US, Hong Kong, Canada, and the UAE. The company has more than 150 academic and industrial collaborations worldwide. For instance, in September 2024, Insilico Medicine collaborated with Inimmune to leverage its proprietary AI platform, Chemistry42, in accelerating the discovery and development of next generation immunotherapeutic.

Exscientia:

Exscientia is an AI-driven small-molecule drug discovery and design company. The company designed and developed an end-to-end solution of AI and experimental technologies for target identification, drug candidate design, translational models, and patient selection. The company’s patient-first AI process comprises four elements, namely, Precision Target (experimental and literature-based AI systems to prioritize projects), Precision Design (an extensive platform of AI technologies to design innovative drugs), Precision Experiment (tech-enabled precision experimentation to derive better data), and Precision Medicine (integrated analysis of patient data to ensure clinical relevance). The platform has helped design candidate drug molecules that have progressed into clinical trials and improve disease understanding through AI-guided assessment and generative AI. Exscientia collaborates with pharmaceutical companies such as GSK, Sanofi, and Roche. The company has offices in the UK, the US, and Japan. For instance, in July 2024, Exscientia announced the expansion of its collaboration with Amazon Web Services, Inc. to utilize AWS’s AI and machine learning services, further enhancing its end-to-end drug discovery and automation platform.

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As ADA Anniversary Approaches, University of Phoenix Survey Highlights AI’s Potential to Advance Accessibility in Work and Learning

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July 24, 2026

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Survey conducted by The Harris Poll on behalf of University of Phoenix finds among those already using AI in the workplace, 60% say AI has improved their knowledge of and ability to use accessibility standards and guidelines.

PHOENIX, July 24, 2026 /PRNewswire/ — As artificial intelligence becomes part of how people work, learn and solve problems, a new University of Phoenix survey conducted by The Harris Poll finds that recent working learners see meaningful opportunities for AI to support accessibility. The survey was designed to understand the impact of AI in the workplace and learning environments on accessibility, defined as ensuring digital content, tools and resources, including AI tools and output, are usable by people with different abilities through inclusive design, use of assistive technology or conformance with accessibility standards, such as the Web Content Accessibility Guidelines (WCAG). The findings are being released ahead of the 36th anniversary of the Americans with Disabilities Act (ADA) on July 26.

The survey, conducted among 1,019 U.S. employed adults who completed a professionally presented training or school course in the past 12 months (“recent working learners”), found that, among workers already using AI in the workplace, 3 in 5 (60%) say AI has improved their knowledge of and ability to use accessibility standards and guidelines, including nearly 1 in 5 (19%) who report significant improvement. 

While the findings point to optimism about AI’s accessibility potential, they also reveal an opportunity for clearer organizational guidance: 45% of respondents say accessibility is absent from, unclear in, or they are uncertain whether it is covered by their workplace AI policies.

“The reality is that accessibility benefits everyone,” shares Kelly Hermann, Vice President of Accessibility and Student Affairs at University of Phoenix. “If accessibility is built in from the beginning, organizations are more likely to create AI-enabled environments that are universally usable. Clearer content, better summaries, accurate captions, and multiple formats can help workers and learners with disabilities, but they also help busy adults, multilingual learners, mobile users, and anyone trying to absorb information quickly.”

Key findings from the survey include:

Workers see AI’s accessibility potential: 89% of recent working learners identify workflows that could benefit from AI and accessibility tools, especially creating accessible documents, presentations, websites or learning materials (38%), presenting information in different formats such as plain language, audio, summaries or translations (33%), and training employees or learners on accessibility practices (30%).AI may help build accessibility awareness: Among those already using AI in the workplace, 60% say AI has improved their knowledge of and ability to use accessibility standards and guidelines.Accessibility is not always clear in workplace AI policies: 45% of recent working learners say accessibility is absent from, unclear in, or they are uncertain whether it is covered by their workplace AI policies.AI tools may not yet fully support different access needs: Among those who use workplace AI tools, only about a quarter of survey respondents (27%) say AI tools available through their workplace or professional learning environment support people with disabilities very well.Human oversight remains important: 36% of recent working learners say human review for important decisions or high-impact work should be part of responsible AI use at work or school.Workers also recognize how AI and accessibility can have an impact on their own career journey: 90% of recent working learners identify AI and accessibility skills that would be valuable in their current or desired career field, including 45% who see value in understanding when AI-generated content needs human review.

Why accessibility is essential to responsible AI adoption

As AI tools are used to draft documents, summarize information, generate captions and transcripts, create image descriptions, support learning and assist with workplace tasks, accessibility becomes central to responsible use. Poorly implemented AI can also create or amplify barriers, including inaccessible content, inaccurate summaries, biased outputs and tools that do not work effectively with assistive technologies.

“Responsible AI is not only about productivity,” Hermann said. “It is about whether the technology works for the people who need to use it. AI can help create more accessible materials and more flexible ways to engage with information, but it still requires clear policies, practical training and human judgment to make sure the outputs are accurate, applicable and usable.”

What the findings mean for employers and educators

The survey suggests that organizations have an opportunity to align AI adoption with supportive design, accessibility practices and workforce training. Employers and educators can take immediate steps by:

Naming accessibility directly in AI policies and guidance.Choosing AI tools with accessibility and assistive technology compatibility in mind.Training workers and learners to create, check and improve accessible AI-generated content.Making support pathways clear for people who experience barriers using AI tools.Keeping human review in place for important decisions, high-impact work and accessibility-sensitive outputs.

The survey also found workers want practical AI training. The most helpful resources identified by recent working learners include real-world examples from their field or industry (36%), hands-on practice using realistic workplace scenarios (34%) and step-by-step demonstrations of common tasks (33%).

Accessibility insights from University of Phoenix

Hermann shared the survey findings ahead of the ADA anniversary in recent media interviews. Hermann oversees the University’s accessibility initiative, including evaluation and remediation of curricular resources, the Center for Access, Resources, Engagement and Support Services (CARES), and the Office of Collaborative Learning and Educational Engagement. Her work focuses on fostering accessible and welcoming educational environments for students, faculty and staff.

Hermann’s office at University of Phoenix also convenes accessibility conversations through initiatives such as Access Amplified™, a free, annual virtual event focused on advancing digital accessibility in web development. The event brings together engineers, developers, designers, content authors and digital strategists for practical strategies and human-centered conversations that address the gap between coding practices and how users with assistive technology experience the web.

About the survey

The survey was conducted online within the United States by The Harris Poll on behalf of University of Phoenix from June 22–29, 2026, among 1,019 employed adults ages 18 and older who have taken a professionally presented training or a school course in the past 12 months, referred to as “recent working learners.” Data were weighted where necessary by age, gender, race/ethnicity, region, education, employment, marital status, household size, household income and smoking status to bring them in line with their actual proportions in the population.

Respondents for this survey were selected from among those who have agreed to participate in surveys. The sampling precision of Harris online polls is measured by using a Bayesian credible interval. For this study, the sample data is accurate to within +/- 3.8 percentage points using a 95% confidence level. This credible interval will be wider among subsets of the surveyed population of interest.

Review the complete survey at phoenix.edu/aiaccessibility.

About University of Phoenix

University of Phoenix is Built for Real Life. 50 Years Strong. The University innovates to help working adults enhance their careers and develop skills in a rapidly changing world through flexible online learning, relevant courses, academic AI pillars, and skills-mapped curriculum for associate, bachelor’s and master’s degree programs. Active students and alumni have access to Career Services for Life® resources including career guidance and tools. For more information, visit phoenix.edu. 

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Mastech Digital to Announce Second Quarter 2026 Financial Results; Participate in Upcoming Investor Conference

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July 24, 2026

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PITTSBURGH, July 24, 2026 /PRNewswire/ — Mastech Digital, Inc. (NYSE American: MHH) (“Mastech Digital”), a leading provider of Digital Transformation IT Services, today announced the date for the release of its financial results for the second quarter ended June 30, 2026, and its participation in an upcoming investor conference.

Second Quarter 2026 Earnings:

Mastech Digital will report its financial results for the second quarter 2026 before the market opens on Thursday, August 6, 2026. Management will host a live conference call and webcast at 9:00 a.m. Eastern Time on that day to discuss the Company’s financial performance and operating results.  The conference call will be hosted by Nirav Patel, President and CEO, and Kannan Sugantharaman, Chief Financial and Operations Officer.

Those wishing to participate via webcast should access the call through Mastech Digital’s Investor Relations website at https://investors.mastechdigital.com. Those wishing to participate via telephone may dial in at 1-800-715-9871 (USA) or 1-646-307-1963 (International) with the passcode 7506988. The replay will be available via webcast through Mastech Digital’s Investor Relations website.

Upcoming Investor Conference:

Mr. Sugantharaman will host a fireside chat at the Sidoti Micro-Cap Investor Conference on Wednesday, August 19, 2026, at 9:15 a.m. Eastern Time.

Mastech Digital management is scheduled to host virtual one-on-one and small group meetings with investors during the conference on August 19-20, 2026. Investors interested in arranging a meeting should contact their Sidoti representative or reach out to the Mastech Digital investor relations team at investors@mastechdigital.com.

About Mastech Digital, Inc.

Mastech Digital (NYSE American: MHH) is a leading provider of Digital Transformation IT Services. The Company offers Data Management, Analytics & AI Solutions, and IT Staffing Services with a digital-first approach. A minority-owned enterprise, Mastech Digital is headquartered in Pittsburgh, PA, with offices across the U.S., Canada, Europe, and India. Visit us at www.mastechdigital.com.

Investor Relations Contact:
investors@mastechdigital.com 

 

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SOLAI Limited Announces Extraordinary General Meeting

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July 24, 2026

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AKRON, Ohio, July 24, 2026 /PRNewswire/ — SOLAI Limited (NYSE: SLAI) (“SOLAI” or the “Company”) (previously known as “BIT Mining Limited”), a technology-driven personal AI and digital infrastructure provider, today announced that it will hold its extraordinary general meeting of shareholders at 428 South Seiberling Street, Akron, Ohio, US on August 14, 2026 at 10:00 a.m., New York time.

Holders of record of ordinary shares and preference shares of the Company at the close of business on July 20, 2026, New York time (the “Record Date”) are entitled to receive notice of, and to attend and vote at, the extraordinary general meeting or any adjournment thereof. Holders of the Company’s American Depositary Shares (“ADSs”) who wish to exercise their voting rights for the underlying ordinary shares must act through the depositary of the Company’s ADS program, Deutsche Bank Trust Company Americas.

The notice of the extraordinary general meeting, which sets forth the resolutions to be submitted to shareholder approval at the extraordinary general meeting is available on the Investor Relations section of the Company’s website at https://ir.solai.com. 

About SOLAI Limited

SOLAI Limited (previously known as “BIT Mining Limited”) (NYSE: SLAI) (previously traded under “BTCM”) is a technology-driven personal AI and digital infrastructure provider. Building upon its historical legacy in digital asset mining and blockchain network operations, the Company is leveraging extensive experience in large-scale hardware deployment, data center operations, and high-performance computing to build the foundational infrastructure for personal AI computing and digital asset ecosystems globally.

For more information:

SOLAI Limited
ir@solai.com
ir.solai.com
www.solai.com 

Christensen Advisory
Jason Ng
Tel: +852-2117-0861
Email: solai@christensencomms.com 

 

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