Global AI For Pharma and Biotech Market - Industry Dynamics, Size, And Opportunity Forecast To 2030

The AI For Pharma and Biotech market is experiencing robust expansion, with market size projected to increase from (1.9 Million) 2023 to (12.9 Million) 2030, demonstrating a consistent year-over-year growth rate of 18.8% AI For Pharma and Biotech Market Size, Share, Competitive Landscape and Trend Analysis Report, by Types (Pharmaceutical companies, Biotechnology startups, Academic institutions, Research organizations, Other), by applications (Drug discovery, Protein engineering, Genomics, Bioinformatics, Other) ,by Technology (Natural Language Processing (NLP), Generative Adversarial Networks (GANs), Variational Auto Encoders (VAEs), Reinforcement Learning, Other) And regions (North America(United States, Canada, Mexico), South America(Brazil, Argentina, Chile, Rest of South America), Europe(Germany, France, Italy, United Kingdom, Benelux, Nordics, Rest of Europe), Asia Pacific(China, Japan, India, South Korea, Australia, Southeast Asia, Rest of Asia-Pacific), MEA(Middle East, Africa)) : Industry Forecast and Opportunity Analysis for 2023 - 2030

The worldwide market for AI in pharma and biotech sectors refers to all the processes right from the development of AI technologies to their practical application in the pharmaceutical and biopharmaceutical fields. The importance of AI-powered solutions is highly appreciated in expediting drug discovery, enhancing clinical trials, bettering patients' health conditions, and even in the production of drugs. These solutions bear the elements of machine learning, natural language processing, and other AI designs to help facilitate the processing of huge signal data for pattern searching and prediction purposes, thus streamlining how drugs are developed and delivered.

AI For Pharma and Biotech Report Highlights

Report Metrics	Details
Forecast period	2019-2030
Base Year Of Estimation	2023
Growth Rate	CAGR of 18.8%
Forecast Value (2030)	USD 12.9 Million
By Product Type	Pharmaceutical companies, Biotechnology startups, Academic institutions, Research organizations, Other
Key Market Players	Atomwise BenevolentAI Deep Genomics DeepMind Ginkgo Bioworks Insilico Medicine Numerate OpenAI Recursion Pharmaceuticals Zymergen
By Region	North America(United States, Canada, Mexico) South America(Brazil, Argentina, Chile, Rest of South America) Europe(Germany, France, Italy, United Kingdom, Benelux, Nordics, Rest of Europe) Asia Pacific(China, Japan, India, South Korea, Australia, Southeast Asia, Rest of Asia-Pacific) MEA(Middle East, Africa)

AI For Pharma and Biotech Market Trends

The market for AI in pharmacy and biotechnology around the world is currently experiencing a major trend in abandonment of traditional methods of drug discovery and development processes with the incorporation of machine learning and data analytics. The use of AI algorithms helps in analyzing numerous data sets, such as genotypic data, results from clinical trials, and even patient data, allowing drug agencies to forecast the effectiveness and safety of a drug with higher accuracy. This is because there are rising pressures to cut costs and time and increase the chances of success of new drugs on the market. An increase in partnerships between pharmaceutical companies and AI-based startups is also witnessed as companies look to bridge the gap between tech and business. Also, IT technologies are becoming more applicable to drug development, with a particular emphasis on the development of bespoke therapy—AI-based treatment, which fits the profile of the very patient populating their database. This not only increases the effectiveness of the treatment but also reduces the side effects of such a treatment, making it more promising for consumers and, which is important, for medical workers. The market is also on the upsurge owing to the upsurge in artificial intelligence investment specifically for the development and research of technology in that sector, such as venture capital funding and government support.

AI For Pharma and Biotech Market Leading Players

The key players profiled in the report are Atomwise, BenevolentAI, Deep Genomics, DeepMind, Ginkgo Bioworks, Insilico Medicine, Numerate, OpenAI, Recursion Pharmaceuticals, Zymergen

Growth Accelerators

Efficiency and cost effectiveness in drug discovery and development have been one of the main drivers for the AI for Pharma and Biotech market worldwide. Traditional R&D processes for pharmaceuticals are time-consuming and costly, with a high failure rate. AI technologies speed up such a process by analyzing huge amounts of data that would take much time to be reviewed, identifying potential drug candidates, and predicting outcomes, thus shortening the timeline from research to market. Especially, it is an important factor of efficiency because the companies strive to get groundbreaking therapies to the patients sooner while in the new landscape left behind by the COVID-19 pandemic. A significant driver is the call for personalised and targeted therapy. AI enables pharma and biotech companies to fully exploit the power of genomic data and patient information in tailoring treatments for every individual's needs and enhanced efficacy with less adverse effect. For instance, regulatory bodies are increasingly looking to support the incorporation of AI into drug development as the approach to healthcare shifts toward value-based care. As such, the adoption of AI solutions will only be progressing with time. Furthermore, developments in machine learning, natural language processing, and data analytics are unlocking insights into complex biological data and are hence improving the quality of the decisions the companies market.

AI For Pharma and Biotech Market Segmentation analysis

The Global AI For Pharma and Biotech is segmented by Type, Application, and Region.
By Type, the market is divided into Distributed Pharmaceutical companies, Biotechnology startups, Academic institutions, Research organizations, Other . The Application segment categorizes the market based on its usage such as Drug discovery, Protein engineering, Genomics, Bioinformatics, Other. Geographically, the market is assessed across key Regions like North America(United States, Canada, Mexico), South America(Brazil, Argentina, Chile, Rest of South America), Europe(Germany, France, Italy, United Kingdom, Benelux, Nordics, Rest of Europe), Asia Pacific(China, Japan, India, South Korea, Australia, Southeast Asia, Rest of Asia-Pacific), MEA(Middle East, Africa) and others, each presenting distinct growth opportunities and challenges influenced by the regions.

Competitive Landscape

The worldwide market for the application of artificial intelligence in pharmaceutical and biotechnological industries is marked by high levels of competition with established participants and new entrants. Notable market players include established tech companies like IBM, Microsoft, and Google, along with AI niche companies’ tailor-made for health sector applications. The market environment is associated with strong rivalry, product variations, and an emphasis on total offers that best fit the needs of the pharmaceutical and biopharmaceutical markets. With the growing need for AI-enabled systems across all health sectors, the market is expected to be active and competitive, with technology and inventions emerging to counter the existing players.

Challenges In AI For Pharma and Biotech Market

The worldwide market for AI in the pharmaceutical and biotechnology sectors is characterized by various challenges, with the most prominent being those relating to data privacy and security. Since the use of AI systems entails the collection and use of clinical data that is predominantly sensitive, compliance with such data protection laws as HIPAA and GDPR becomes a necessity. Companies have to operate within intricate data governance structures while undertaking measures to mitigate various cyber threats that could compromise data integrity, especially because such incidences could damage the reputation of the company and attract legal action. The requirement to provide transparency and interpretability of the algorithms is another hurdle. Biotech and pharmaceutical industries need to ensure that when such AI systems are adopted, there are ways to explain the conclusions made through such systems or AI-based systems, especially if the area of usage is drug fabrication or patient management. There is concern about how easy it would be for stakeholders to address issues of responsibility given that most AI models are black boxes, and this may deter their uptake.

Risks & Prospects in AI For Pharma and Biotech Market

The global market for AI applications in the pharmaceutical and biotechnology industry has tremendous potential owing to the growing need for more efficient drug development processes. AI can independently conduct drug research by simulating vast amounts of already available data, especially in modelling drug-drug interactions and drug-target interactions. It is obvious that this not only shortens the periods of drug development but also saves a lot of money, which is beneficial for the pharmaceutical companies that are always in search of ways to raise their R&D output. Besides that, the forecast shows that the market will develop owing to the growth of the demand for personalised medicine and targeted therapy. AI tools can be used to process patient information for the purposes of each profile, making it possible to enhance the treatment efficiency and effectiveness of the therapy. Policymakers are also changing their stance on AI-related approaches, endorsing their use in drug development, making the market even more conducive to growth. As demand for digital transformation within the healthcare sector increases, so does the potential for use of AI in clinical trial activities, patient follow-up, and drug manufacture, portraying its relevance to the future of pharma and biotech industries.

Key Target Audience

The audience of interest in the global market for AI in pharma and biotech industries comprises pharmaceutical and biotechnology companies and drug discovery and development research institutions. The aforementioned stakeholders use AI tools to optimize processes of carrying out research, augment cognitive abilities with respect to analytics, for instance forecasting burning trends in medical studies, and fine-tune the designs of clinical trials. The rationale behind that is reduction of development costs, speeding up the launch of new treatment regimens, and enhanced patient care with the use of personalized medicine solutions.,, Moreover, the market also includes healthcare systems and the government that demand the use of large datasets and require the results of sophisticated analyses in the course of decision implementation and monitoring. AI solutions can assist in the continuous evaluation of clinical trial data to make sure that all necessary actions for regulatory compliance are taken and assure improved safety. Finally, a section of the target audience includes investors and venture capital firms focusing on new technology, since they are interested in potential artificial intelligence applications in pharmaceuticals and biotechnology that would provide an advantage in a fast-changing market.

Merger and acquisition

Recent integrations and consolidations within the global pharmaceutical and biotechnology artificial intelligence market have illustrated noticeable correlations and connotations with the enhancement of partnerships and collaborations for drug discovery and development processes. For instance, in January 2024, Eli Lilly announced its plans to acquire Morphic, a company focused on advanced small-molecule inhibitors for inflammatory bowel disease, for the sum of $3.2 billion. In the same manner, Bristol Myers Squibb partnered with VantAI in order to employ AI in advancing drug development, further reflecting the trend on using technology to enhance the biopharma pipeline‘s productivity. The trend of increasing deal value could also be observed in the market, as the year 2023 proved to be a reasonable recovery reaching to about more than $152 billion and directed towards transactions that are larger and more de-risked than those that existed before. Every company has a strong interest in acquiring research candidates or in-licensed technologies, especially within the oncology and the central nervous system infusion areas, as they seek to cement strong positions amid intense competition. More collaborations are anticipated as the AI space becomes more entrenched in biotech, as there will be a need for quicker and better solutions for drug development.