Global AI-based Drug Discovery Market (2022 to 2035) - by Drug Discovery Steps, Therapeutic Area and Key Geographies - ResearchAndMarkets.com

DUBLIN--(BUSINESS WIRE)--The "AI-based Drug Discovery Market: Distribution by Drug Discovery Steps, Therapeutic Area and Key Geographies: Industry Trends and Global Forecasts, 2022-2035" report has been added to ResearchAndMarkets.com's offering.

This report features an extensive study of the current landscape and future potential of the players engaged in offering AI-based services, platforms and tools for the discovery of novel drug candidates. The study features an in-depth analysis, highlighting the capabilities of AI-based drug discovery service / technology providers.

The discovery and development process of a novel therapeutic candidate is often tedious and fraught with several challenges. The key concern associated with the overall process is the high attrition rate, which is often attributed to the trial-and-error approach followed for the drug discovery process. In fact, only a small proportion of pharmacological leads are translated into viable product candidates for clinical studies. In addition, experts believe that close to 90% of the product candidates considered in such studies fail to advance further in the development process.

This, in turn, often results in a massive financial burden. In this context, it is estimated that a prescription drug takes around 10 to 15 years and an average investment of USD 1 to 2 billion, in order to traverse from the bench to the market. Moreover, around one-third of the aforementioned expenditure is incurred during the drug discovery phase alone. Therefore, to address the existing concerns, such as rising capital requirements and failure of late-stage programs, pharmaceutical players are currently exploring the implementation of Artificial Intelligence (AI) based tools to better inform their discovery and development operations, using available chemical and biological data.

Specifically, AI is believed to be capable of processing and analyzing large volumes of clinical / medical data, as well as leverage it to better inform modern drug discovery efforts. In this context, deep learning algorithms have been demonstrated to be able to cross-reference published scientific literature (structured data) with electronic health records (EHRs) and clinical trial information (unstructured data), in order to generate actionable insights for target identification, hit generation and lead optimization.

At present, machine learning, deep learning, supervised learning, unsupervised learning and natural language processing are some of the key AI-based tools being deployed across different processes, including drug discovery, within the healthcare sector. The use of AI-enabled technologies in drug discovery operations is expected to not only improve the overall R&D productivity, but also reduce clinical failure of product candidates, by enabling accurate prediction of its safety and efficacy during early stages of development. Close to 210 companies currently claim to offer AI-based services, platforms and tools for drug discovery.

Further, over USD 10 billion has been invested in this market by both private and public sector investors, in the last five years. Interestingly, close to 50% of the aforementioned amount was invested in the last two years, reflecting the increasing interest of stakeholders in AI-based tools for drug discovery.

Additionally, close to 440 recently instances of collaborations have been reported between industry / academic stakeholders in order to advance the development of various AI-based solutions for drug discovery. Considering the active initiatives being undertaken by players based in this domain, we are led to believe that the opportunity for stakeholders in this niche, albeit upcoming, industry is likely to grow at a commendable pace in the foreseen future.

Companies Mentioned

• 3BIGS
• 3W Healthcare Fund
• 3W Partners
• 4B Technologies
• 5Y Capital
• 6 Dimensions Capital
• 8VC
• 99andBeyond
• A2A Pharmaceuticals
• A2i Therapeutics
• AARP Foundation
• AbbVie
• AbCellera
• Absci
• Abstract Ventures
• Accelerate Long Island
• Accenture
• Accutar Biotech
• Acellera
• Acequia Capital
• Acerand Therapeutics
• ACF Investors
• AcuraStem
• Adagene
• Adare Pharma Solutions
• ADC Therapeutics
• ADEL
• adMare BioInnovations
• Advantage Capital
• And Many More Companies!

Key Questions Answered

• Who are the leading players engaged in the AI-based drug discovery market?
• Which of the key AI technologies are presently being most commonly adopted by drug discovery focused companies?
• What is the likely valuation / net worth of companies engaged in this domain?
• What is the likely cost saving potential associated with the use of AI in the drug discovery process?
• How is the intellectual property landscape for AI-based drug discovery technologies likely to evolve in the foreseen future?
• Which partnership models are most commonly adopted by stakeholders engaged in this industry?
• What is the overall trend of funding and investments within this domain?
• How is the current and future opportunity likely to be distributed across key market segments?

Key Topics Covered:

1. PREFACE

2. EXECUTIVE SUMMARY

3. INTRODUCTION

4. COMPETITIVE LANDSCAPE

5. COMPANY PROFILES: AI-BASED DRUG DISCOVERY PROVIDERS IN NORTH AMERICA

6. COMPANY PROFILES: AI-BASED DRUG DISOCVERY SERVICE PROVIDERS IN EUROPE

7. COMPANY PROFILES: AI-BASED DRUG DISOCVERY SERVICE PROVIDERS IN ASIA PACIFIC

8. PARTNERSHIPS AND COLLABORATIONS

9. FUNDING AND INVESTMENT ANALYSIS

10. PATENT ANALYSIS

11. PORTER'S FIVE FORCES ANALYSIS

12. COMPANY VALUATION ANALYSIS

13. AI-BASED HEALTHCARE INITIATIVES OF TECHNOLOGY GIANTS

14. COST SAVING ANALYSIS

15. MARKET FORECAST

16. CONCLUSION

17. EXECUTIVE INSIGHTS

18. APPENDIX I: TABULATED DATA

19. APPENDIX II: LIST OF COMPANIES AND ORGANIZATIONS

For more information about this report visit https://www.researchandmarkets.com/r/45jaqy

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