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Artificial Intelligence For Drug Discovery Market

Artificial Intelligence For Drug Discovery,Biomarker Development and Advanced R and D Landscape Overview Q2 2018


Artificial Intelligence For Drug Discovery, Biomarker Development and Advanced R&D Landscape Overview Q2/2018 offers comprehensive coverage of the current state of the AI in Drug Discovery industry landscape, featuring chapters on the history, current state and near future of the industry, regional and subsector-specific competutive and comparative analyses, and profiles of 100 Companies, 220 Investors, 15 Biopharma, 15 IT/Tech Corporations, and 20 leading R&D Centres active in the AI for Drug Discovery space. Section I delivers a summary of the most important recent industry events, including coverage of the most important BioPharma and IT/Tech corporations active in the space, government initiatives aiming to accelerate the dynamic of industry progress in the USA, UK, EU and Asia-Pacific region, industry-specific conferences and journalists, and a regional comparison of industry activity that summarizes which countries are currently at the forefront of activity, which ones are lagging behind, and which ones are showing evidence of rapidly increasing activity in the years to come. Section II  provides in-depth coverage of the science and technology behind the industry, analysis of emerging subsectors and new application within the industry (including the convergence of AI with blockchain, digital medicine and Longevity technologies), and finally, a near-future forecast of industry growth and diversification from 2019 to 2020. Section III: Comparative Industry Analysis & Classification Framework (Investor and M&A Guide), 70 pages in length, a section specifically tuned to industry professionals such as investors, analysts, BioPharma/Tech executives and decision-makers, is available for purchase. This section is devoted to an in-depth comparative and quantitative analysis of the entire AI for Drug Discovery landscape, utilizing advanced infographics and tangible parameters both for (1) ranking various AI for Drug Discovery companies according to their levels of scientific validation, clinical development, R&D and industry-application diversification, and overall prospects for future growth and for (2) classifying AI for Drug Discovery companies according to their type and number of distinct industry applications, proportion of AI specialists, number of patents and publications, use of next-generation AI technologies (e.g. GANs vs ML), and whether they utilize AI as a core component of their R&D or as a complementary element to enhance their primary, non-AI focus and business model. 
Companies Mentioned:
 AccutarBio, 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, Mendel.ai, Meta, Micar21, Mind the Byte, nference, Novoheart, nQ Medical, NuMedii, Numerate, Nuritas, Owkin, PathAI, Pepticom, Peptone, Pharnext, Phenomic AI, Plex Research, ProteinQure, Qrativ, Quantitative Medicine, Recursion Pharmaceuticals, Resonant Therapeutics, Reveal Biosciences, Reverie Labs, ReviveMed, sciNote, Sparrho, Spring Discovery, Standigm, Structura Biotechnology, Synthace, TeselaGen, ThoughtSpot, Transcriptic, Trials.ai, TwoXAR, Verge Genomics, Virogin, Virvio, WinterLight Labs, XtalPi	
AI for Drug Discovery Landscape Mind Maps - pp. 4; Executive Summary - pp. 8; Introduction: Background and Fundamentals of AI for Drug Discovery Industry - pp. 21; Section I:     AI for Drug Discovery Landscape Overview (Industry Developments Q2 2018) - pp. 43; Chapter I:     Landscape of AI for R&D and Drug Discovery Q2 2018 - pp. 46; Chapter II:    Regional Comparison: USA, UK, EU and Asia-Pacific - pp. 73; Chapter III:   Trends of Investment and M&A Deals - pp. 85; Chapter IV:   BioPharma Corporations Onboarding AI for Drug Discovery - pp. 95; Chapter V:    IT & Tech Corporations Entering the AI for Drug Discovery Space - pp. 124; Chapter VI:   Government Initiatives - pp. 141; Chapter VII:  Industry-Specific Media & Conferences - pp. 157; Section III:   Comparative Industry Analysis & Classification Framework (Investor and M&A Guide) - pp. 224; Chapter XI:   Classification/Ratings of AI for Advanced R&D and Drug Discovery Companies - pp. 226; Chapter XII:  2010-2016 - Investment Rounds, M&A Deals and Notable Events - pp. 249; Chapter XIII: 2017 - Investment Rounds, M&A Deals and Notable Events - pp. 259; Chapter XIV: Q1 2018 - Investment Rounds, M&A Deals and Notable Events - pp. 269; Chapter XV:  Q2 2018 - Investment Rounds, M&A Deals and Notable Events - pp. 278

	

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