AI for Drug Discovery, Bio-Marker Development and Advanced R&D Landscape Overview 2018 / Q2

  • ID: 4607090
  • Report
  • 637 Pages
  • Deep Knowledge Analytics
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FEATURED COMPANIES

  • 11.2 Capital
  • BullFrog AI
  • EPIC Capital
  • Innoplexus
  • Novoheart
  • Sofinnova Partners
  • MORE

The second quarter of 2018 saw major changes, significant investments, acquisitions, and the establishment of substantial joint ventures. This serves as a stark reminder of how fast the AI for Drug Discovery, Biomarker Development and Advanced R&D sector is advancing. Many trends noted in our last report have continued and intensified, while other new trends have emerged as well.

The report is structured in such a way as to meet the needs of different kinds of readers and stakeholders according to their specific interests and specialisation. It includes both broad chapters that describe the underlying fundamentals of different areas of the AI for Drug Discovery sphere, as well as chapters that give specific attention to industry trends and developments, and chapters that provide comparative analyses of companies, investors, R&D centers, IT, Tech and pharma corporations.

  • The report begins with several infographic MindMaps that deliver an understanding of the scope of the industry landscape at a single glance, including segmentation (by application and by region) of companies, investors and R&D centers.
  • The report’s Executive Summary charts the major trends and significant developments that have occurred in the industry during the second quarter of 2018.
  • The report's Introduction (Background and Fundamentals of AI for Drug Discovery) lays the groundwork and background for an understanding of its more specialized chapters, offering a basic introduction to AI in Drug Discovery, the broader AI in healthcare industry, the specific factors that cause resistance to change in the BioPharma industry, and an introduction into the ways in which IT and Tech corporations are entering the sphere of AI in Drug Discovery.

Section I: AI for Drug Discovery Landscape Overview (Industry Developments Q2 2018) provides a detailed overview of the entire AI for Drug Discovery landscape in Q2 of 2018, discussing trends in investments and M&A deals, BioPharma on-boarding AI for Drug Discovery into their own internal activities, the entry of IT and Tech corporations into the space, government initiatives aiming to put certain countries on the forefront of the industry in the years to come, and industry-specific conferences and media coverage.

Chapter I: Landscape of AI for R&D and Drug Discovery Q2 2018 aggregates, lists and categorizes the various different organizations and entities that are profiled in greater detail in the Appendices of the report. It features lists (which break down each type of entity according to industry segmentation/application and location) of 100 companies, 230 investors, 20 leading R&D centers, 25 corporations (10 BioPharma corporations and 15 IT & Tech corporations), 20 industry-specific conferences and 20 journalists writing on the topic of AI for Drug Discovery.

Chapter II: Regional Comparison: USA, UK, EU and Asia-Pacific delivers a comparative analysis of AI for Drug Discovery companies, investors, corporations (IT & Tech corporations and BioPharma corporations active within the field) and conferences, in order to give readers an idea of the comparative levels of activity and growth of the industry in specific regions.

Chapter III: Trends of Investment and M&A Deals gives a broad overview of trends in investments and M&A deals specifically tuned to industry progress in Q2 of 2018, detailing an overall increase in investments, the active participation BioPharma corporations (largely in the form of joint ventures with AI and AI for Drug Discovery companies), the increasing activity of IT and Tech corporations, and the surge of activity from Chinese investors and Tech corporations.

Chapter IV: BioPharma Corporations Onboarding AI for Drug Discovery discusses the major occurrences happening in the BioPharma sector, and outlines how the BioPharma industry is now actively participating in the AI for Drug Discovery and biomarker development space via internal R&D, investment and acquisition, in contrast to 2017, during which time they remained largely skeptical of the disruptive impact of AI.

Chapter V: IT & Tech Corporations Entering the AI for Drug Discovery Space details how IT & Tech Corporations are continuing to enter the space; this was already a major trend in 2017, and it is continuing apace into 2018, remaining one of the strongest hallmarks of the subsector’s exponential dynamic of development.

Chapter VI: Government Initiatives gives specific coverage of various AI for Drug Discovery government initiatives launched over the past several years in the USA, UK, EU and Asia-Pacific region, all of which aim to utilize industry and government partnerships in order to secure each nation's position as a leader in AI for Drug Discovery over the course of the next several years. It gives particular focus to the number of new initiatives that were launched in 2018.

Chapter VII: Industry-Specific Media & Conferences charts the industry-specific conference and media landscape. It lists 20 conferences dedicated to AI in Drug Discovery and analyzes some of the most predominant conference topics and trends, and gives attention to the fact that, in addition to the overall increase in the number of conferences dedicated specifically to the topic, 2018 is also witnessing the inclusion of an AI for Drug Discovery track, session, forum or panel in the majority of the leading traditional BioPharma conferences aimed at major pharmaceutical executives. It also lists 20 journalists who are regularly reporting on the topic of AI for Drug Discovery, and who possess a certain minimum level of expertise on the topic, outlining some of the major trends and topics dominating media coverage of the industry.

Section II: Novel Technologies & Trends (Industry Forecast 2019-2020) is devoted to in-depth coverage of the science and technology behind the industry, and to analysis of emerging subsectors within the industry, charting the near future of the industry from 2019 to 2020.

Chapter VIII: Deep Learning in Drug Discovery gives an in-depth overview of topics, trends and advancements occurring in deep learning for drug discovery, one of the specific forms of AI which has now emerged as the leading technology delivering practical and tangible results in the industry, and pays particular attention to the emergence of Generative Adversarial Networks (GANs) as a highly disruptive sub-class of deep learning that may come to dominate industry progress in the years to come.

Chapter IX: Longevity Research (AI and Advanced R&D) is devoted to the use of AI in Drug Discovery for Longevity research, which can be considered to have started in mid-2017 with an event held at the Buck Institute for Research on Aging, at which Atomwise, BioAge and Insilico Medicine held a workshop, and which has just recently been formally solidified through Insilico Medicine being awarded the 2018 North American Artificial Intelligence for Aging Research and Drug Development Technology Innovation Award by leading business consulting firm Frost & Sullivan.

Chapter X: Next Generation AI, convergence with Blockchain and Digital Medicine charts the ongoing convergence of AI for Drug Discovery with other advanced technologies including blockchain, personalised medicine and digital medicine, illustrating how these technologies and industries are being synergistically integrated so as to expedite the dynamic of progress in the AI for Drug Discovery sphere.

Section III: Comparative Industry Analysis & Classification Framework (Investor and M&A Guide) is devoted to an in-depth comparative and quantitative analysis of the entire AI for Drug Discovery landscape, specifically tuned for investors, business analysts and decision makers who wish to gain a deeper understanding of the industry in Q2 of 2018

Chapter XI: Comparison of Leading AI Companies directs its attention to the most active and scientifically validated AI for Drug Discovery companies, and details their activities side by side. The chapter also performs a quantitative analysis of many of the AI for Drug Discovery companies covered and profiled in this report using of a variety of tangible metrics that can be used to acquire an understanding of their level of scientific validation and industry activity, including the proportion of AI specialists among their total staff, number of publications, number of patents, etc. It then uses these metrics to rank AI for Drug Discovery companies side by side, and to build a classification framework by which these companies can be better categorized according to their specific focus, application and industry segmentation.

Chapter XII: 2010 - 2016 - Investment Rounds, M&A Deals and Notable Events summarizes some of the most notable investment rounds, M&As and other notable events from 2010-2016, including but not limited to Benevolent AI's $87M raise, ThoughtSpot's $100M raise and Meta's $23M raise.

Chapter XIII: 2017 - Investment Rounds, M&A Deals and Notable Events summarizes some of the most notable investment rounds, M&As and other notable events in 2017, including but not limited to Exscientia's €250M raise, AiCure's $15M raise and Insilico Medicine's $10M raise.

Chapter XIV: Q1 2018 - Investment Rounds, M&A Deals and Notable Events summarizes some of the most notable investment rounds, M&As and other notable events in Q1 of 2018, including but not limited to AtomWise's $45M raise, XtalPi's $15M raise, and twoXAR's $10M raise.

Chapter XV: Q2 2018 - Investment Rounds, M&A Deals and Notable Events summarizes the major investments, M&As and other notable events (e.g. joint ventures, public announcements, etc.) that have occurred within the AI for Drug Discovery space specifically in Q2 of 2018, including but not limited to ThoughtSpot's $145M raise, Benevolent.AI's $115M raise, Celsius Therapeutics' $65M raise, and Datavant's $40.5M raise.

This current edition considers the industry landscape in greater depth than our previous reports, and provides updated profiles of the companies, investors and influencers comprising the industry. It also features several new chapters, including a chapter dedicated to IT and Tech corporations into the AI for Drug Discovery space, the continuing entry of BioPharma corporations into the industry, and an entirely new section -- Section III: Comparative Industry Analysis & Classification Framework (Investor and M&A Guide) - that delivers an extended and comprehensive comparative analysis of AI for Drug Discovery companies by industry segmentation, level of scientific validation and location.

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FEATURED COMPANIES

  • 11.2 Capital
  • BullFrog AI
  • EPIC Capital
  • Innoplexus
  • Novoheart
  • Sofinnova Partners
  • MORE
  • AI for Drug Discovery Landscape Mind Maps
  • Executive Summary
  • Introduction: Background and Fundamentals of AI for Drug Discovery Industry
  • Section I: AI for Drug Discovery Landscape Overview (Industry Developments Q2 2018)
  • Chapter I: Landscape of AI for R&D and Drug Discovery Q2 2018
  • Chapter II: Regional Comparison: USA, UK, EU and Asia-Pacific
  • Chapter III: Trends of Investment and M&A Deals
  • Chapter IV: BioPharma Corporations Onboarding AI for Drug Discovery
  • Chapter V: IT & Tech Corporations Entering the AI for Drug Discovery Space
  • Chapter VI: Government Initiatives
  • Chapter VII: Industry-Specific Media & Conferences
  • Section II: Novel Technologies & Trends (Industry Forecast 2019 2020)
  • Chapter VIII: Deep Learning in Drug Discovery
  • Chapter IX: Longevity Research (AI and Advanced R&D)
  • Chapter X: Next Generation AI, convergence with Blockchain and Digital Medicine
  • Section III: Comparative Industry Analysis & Classification Framework (Investor and M&A Guide)
  • Chapter XI: Classification/Ratings of AI for Advanced R&D and Drug Discovery Companies
  • Chapter XII: 2010-2016 - Investment Rounds, M&A Deals and Notable Events
  • Chapter XIII: 2017 - Investment Rounds, M&A Deals and Notable Events
  • Chapter XIV: Q1 2018 - Investment Rounds, M&A Deals and Notable Events
  • Chapter XV: Q2 2018 - Investment Rounds, M&A Deals and Notable Events
  • Appendix / Profiles
  • 100 Companies Applying AI for Drug Discovery and Advanced R&D
  • 20 Leading R&D centers
  • 15 BioPharma Corporations Using Artificial Intelligence for Drug Discovery
  • 15 Tech Corporations interested in Advanced AI applications in Healthcare
  • 220 Investors in AI for Drug Discovery
  • Disclaimer
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  • Acurastem
  • AiCure
  • Antidote
  • Arbor Biotechnologies
  • Athelas
  • ATOM
  • Atomwise
  • Bactevo
  • BenchSci
  • BenevolentAI
  • Berg LLC
  • BioAge Labs
  • Biorelate
  • BioSymetrics
  • Biovista
  • BioXcel
  • Brite Health
  • BullFrog AI
  • C4X discovery
  • Cambridge Cancer Genomics
  • Celsius Therapeutics
  • Clinithink
  • Cloud Pharmaceuticals
  • CloudMedX
  • Cotinga Pharmaceuticals
  • Cyclica
  • CytoReason
  • Cytox
  • Datavant
  • Deep 6 AI
  • Deep Genomics
  • Desktop Genetics
  • e-therapeutics
  • Emerald Cloud Lab
  • Engine Biosciences
  • Envisagenics
  • Euretos
  • EvidScience
  • exscientia
  • FDNA
  • Globavir
  • GNS Healthcare
  • GTN
  • Healx
  • HelixAI
  • IBM Watson Health
  • Iktos
  • Imagia
  • Inato
  • Innoplexus
  • Insilico Medicine
  • Insitro
  • Intellegens
  • Iris.ai
  • Juvenescence AI
  • Kyndi
  • Lantern Pharma
  • MediBIC Group
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  • Meta
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  • PathAI
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  • Phenomic AI
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  • ProteinQure
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  • Quantitative Medicine
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  • Resonant Therapeutics
  • Reveal Biosciences
  • Reverie Labs
  • ReviveMed
  • sciNote
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  • Spring Discovery
  • Standigm
  • Structura Biotechnology
  • Synthace
  • TeselaGen
  • ThoughtSpot
  • Transcriptic
  • Trials.ai
  • TwoXAR
  • Verge Genomics
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  • XtalPi
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