表紙:プレシジョンメディシンソフトウェア開発者の世界市場:治療対象の疾患別 (腫瘍性疾患、心血管疾患、神経障害、代謝障害)、主要地域別 (北米、欧州、アジア太平洋)
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商品コード
1063757

プレシジョンメディシンソフトウェア開発者の世界市場:治療対象の疾患別 (腫瘍性疾患、心血管疾患、神経障害、代謝障害)、主要地域別 (北米、欧州、アジア太平洋)

Precision Medicine Software Developers Market by Target Therapeutic Indication (Oncological Disorders, Cardiovascular Disorders, Neurological Disorders, Metabolic Disorders), Key Geographical Regions (North America, Europe, Asia-Pacific)

出版日: | 発行: Roots Analysis | ページ情報: 英文 176 Pages | 納期: 即日から翌営業日

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プレシジョンメディシンソフトウェア開発者の世界市場:治療対象の疾患別 (腫瘍性疾患、心血管疾患、神経障害、代謝障害)、主要地域別 (北米、欧州、アジア太平洋)
出版日: 2022年01月31日
発行: Roots Analysis
ページ情報: 英文 176 Pages
納期: 即日から翌営業日
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  • 概要
  • 図表
  • 目次
概要

当レポートでは、世界のプレシジョンメディシンソフトウェア開発者の市場について分析し、技術・市場の特徴 (主な治療領域ほか) や、昨今の資本取引・事業戦略の傾向 (2018年~2021年)、全体的な市場規模の動向見通し、治療領域別・地域別・エンドユーザーの種類別の詳細動向、主要企業のプロファイル、といった情報を取りまとめてお届けいたします。

本文中の図表サンプル

目次

第1章 序論

第2章 エグゼクティブサマリー

第3章 イントロダクション

  • 分析概要
  • プレシジョンメディシンの概要
    • プレシジョンメディシンの進化
    • プレシジョンメディシンにおける新しいアプローチ
  • 主要な技術プラットフォーム
    • クラウドベース
    • オンプレミス
  • プレシジョンメディシンソフトウェアの開発者が直面する主な課題
    • 前例のないデータ量
    • 膨大な個人レベルデータの解釈
    • 臨床でのソリューションの組み込み
  • 活用領域
    • 治療領域
    • ファーマコゲノミクス
  • 従来の治療法に対するプレシジョンメディシンの利点
    • 患者のメリット
    • 医療提供者のメリット
  • 今後の展望

第4章 市場情勢

  • 分析概要
  • プレシジョンメディシンソフトウェア開発者:全体的な市場情勢
    • 設立年別の分析
    • 企業規模別の分析
    • 地域別の分析
    • プラットフォームの種類別の分析
    • ソフトウェアアプリケーションの目的別の分析
    • 処理データの種類別の分析
    • 治療領域別の分析
    • エンドユーザーの種類別の分析
  • 重要な洞察

第5章 企業プロファイル

  • 分析概要
  • プレシジョンメディシンソフトウェア開発者
    • Ariel Precision Medicine
    • C2i Genomics
    • Genedata
    • Inspirata
    • IQVIA
    • SAP
  • 追加のプロファイル
    • Fabric Genomics
    • GenomOncology
    • Human Longevity
    • SOPHiA GENETICS
    • Syapse

第6章 企業競争力の分析

  • 分析概要
  • 主なパラメータ
  • 調査手法
  • 企業の競争力分析:プレシジョンメディシンソフトウェア開発者
    • 企業競争力の分析:大企業・巨大企業
    • 企業競争力の分析:中規模企業
    • 企業競争力の分析:小規模企業

第7章 特許分析

  • 分析概要
  • 調査範囲・手法
  • プレシジョンメディシンソフトウェア開発者:特許分析

第8章 事業提携と事業協力

  • 分析概要
  • 事業提携のモデル
  • プレシジョンメディシンソフトウェア開発者:最近の事業提携・事業協力

第9章 資金調達・投資の分析

  • 分析概要
  • 資金の種類
  • プレシジョンメディシンソフトウェア開発者:資金調達・投資の分析

第10章 魅力度・競争力 (AC) マトリックス

  • 分析概要
  • ACマトリックス:概要
    • 強力な事業セグメント
    • 平均的な事業セグメント
    • 弱い事業セグメント

第11章 市場予測

  • 分析概要
  • 予測分析の手法と前提条件
  • 世界のプレシジョンメディシンソフトウェア開発者市場 (2021年~2031年)
  • プレシジョンメディシンソフトウェア開発者市場:治療分野別の分析 (2021年~2031年)
    • 腫瘍性疾患
    • 心血管疾患
    • 神経障害
    • 代謝障害
  • プレシジョンメディシンソフトウェア開発者市場:地域別の分析 (2021年~2031年)
    • 北米
    • 欧州
    • アジア太平洋
  • プレシジョンメディシンソフトウェア開発者市場:エンドユーザーの種類別の分析 (2021年~2031年)
    • 医療提供者向け
    • 研究・政府機関向け
    • 製薬・バイオテクノロジー企業向け

第12章 SWOT分析

  • 分析概要
  • 強み
  • 弱点
  • 機会
  • 脅威
  • SWOT要因の比較
  • 結論

第13章 結論

第14章 付録I:集計データ

第15章 付録II:企業一覧

図表

List Of Tables

  • Table 4.1. Precision Medicine Software Developers: Information on Year of Establishment, Company Size and Location of Headquarters
  • Table 4.2. Precision Medicine Software Applications: Information on Software Applications, Status of Software Applications, HIPAA Compliance
  • Table 4.3. Precision Medicine Software Applications: Information on Software Applications Specification and Software Applications Purpose
  • Table 4.4. Precision Medicine Software Applications: Information on Type of Data Handled
  • Table 4.5. Precision Medicine Software Applications: Information on Therapeutic Area
  • Table 4.6. Precision Medicine Software Applications: Information on Type of End-User
  • Table 5.1. SAP: Company Overview
  • Table 5.2. SAP: Product Portfolio
  • Table 5.3. IQVIA: Company Overview
  • Table 5.4. IQVIA: Product Portfolio
  • Table 5.5. IQVIA: Recent Developments and Future Outlook
  • Table 5.6. Inspirata: Company Overview
  • Table 5.7. Inspirata: Product Portfolio
  • Table 5.8. Genedata: Company Overview
  • Table 5.9. Genedata: Product Portfolio
  • Table 5.10. Genedata: Recent Developments and Future Outlook
  • Table 5.11. Ariel Precision Medicine: Company Overview
  • Table 5.12. Ariel Precision Medicine: Product Portfolio
  • Table 5.13. Ariel Precision Medicine: Recent Developments and Future Outlook
  • Table 5.14. C2i Genomics: Company Overview
  • Table 5.15. C2i Genomics: Product Portfolio
  • Table 5.16. C2i Genomics: Recent Developments and Future Outlook
  • Table 5.17. Syapse: Company Overview
  • Table 5.18. Syapse: Product Portfolio
  • Table 5.19. Syapse: Recent Developments and Future Outlook
  • Table 5.20. Fabric Genomics: Company Overview
  • Table 5.21. Fabric Genomics: Product Portfolio
  • Table 5.22. GenomOncology: Company Overview
  • Table 5.23. GenomOncology: Product Portfolio
  • Table 5.24. SOPHiA GENETICS: Company Overview
  • Table 5.25. SOPHiA GENETICS: Product Portfolio
  • Table 5.26. SOPHiA GENETICS: Recent Developments and Future Outlook
  • Table 5.27. Human Longevity: Company Overview
  • Table 5.28. Human Longevity: Product Portfolio
  • Table 5.29. Human Longevity: Recent Developments and Future Outlook
  • Table 7.1. Patent Analysis: List of Top CPC Symbols
  • Table 7.2. Patent Analysis: Summary of Benchmarking Analysis
  • Table 7.3. Patent Analysis: Information on Patent Categorization based on Weighted Scores
  • Table 7.4. Patent Analysis: List of Leading Patents (in terms of highest relative valuation)
  • Table 8.1. Partnerships and Collaborations: Information on Partner, Year of Partnership, and Type of Partnership, 2018-2021
  • Table 8.2. Partnerships and Collaborations: Information on Focus Area and Therapeutic Area
  • Table 9.1. Fundings and Investments: Information on Type of Funding, Year of Investment, Amount Invested and Lead Investors, 2018-2021
  • Table 9.2 Funding and Investment Analysis: Summary of Investments
  • Table 9.3 Funding and Investment Analysis: Summary of Venture Capital Round
  • Table 9.4 Fundings and Investments: Information on Year of Funding, Location of Headquarters of Recipients, Software Applications, Type of Software Applications and Focus Area
  • Table 14.1. Precision Medicine Software Developers: Distribution by Year of Establishment
  • Table 14.2. Precision Medicine Software Developers: Distribution by Company Size
  • Table 14.3. Precision Medicine Software Developers: Distribution by Region
  • Table 14.4. Precision Medicine Software Developers: Distribution by Location of Headquarters
  • Table 14.5. Precision Medicine Software Developers: Distribution by Company Size and Region
  • Table 14.6. Precision Medicine Software Developers: Distribution by Year of Establishment, Company Size and Region
  • Table 14.7. Precision Medicine Software Developers: Distribution by Type of Platform
  • Table 14.8. Precision Medicine Software Developers: Distribution by Purpose of Software Applications
  • Table 14.9. Precision Medicine Software Developers: Distribution by Type of Data Handled
  • Table 14.10. Precision Medicine Software Developers: Distribution by Therapeutic Area
  • Table 14.11. Precision Medicine Software Developers: Distribution by Type of Data Handled and Therapeutic Area
  • Table 14.12. Precision Medicine Software Developers: Distribution by Regulatory Accreditation Received
  • Table 14.13. Precision Medicine Software Developers: Distribution by Status of Software Applications
  • Table 14.14. Precision Medicine Software Developers: Distribution by Status of Software Applications and Region
  • Table 14.15. Precision Medicine Software Developers: Distribution by Therapeutic Area and Status of Software Applications
  • Table 14.16. Precision Medicine Software Developers: Distribution by Type of Data Handled and Status of Software Applications
  • Table 14.17. Precision Medicine Software Developers: Distribution by Type of End-User
  • Table 14.18. Precision Medicine Software Developers: Most Active Players: Distribution by Number of Software Applications
  • Table 14.19. Company Competitiveness: Small Companies
  • Table 14.20. Company Competitiveness: Mid-sized Companies
  • Table 14.21. Company Competitiveness: Large and Very Large Companies
  • Table 14.22. Company Competitiveness: Companies in North America
  • Table 14.23. Company Competitiveness: Companies in Europe, Asia-Pacific and RoW
  • Table 14.24. Company Competitiveness: Most Active Players
  • Table 14.25. Patent Analysis: Distribution by Type of Patent
  • Table 14.26. Patent Analysis: Distribution by Publication Year
  • Table 14.27. Patent Analysis: Distribution of Granted Patents by Publication Year
  • Table 14.28. Patent Analysis: Distribution by Geography (Continent-wise)
  • Table 14.29. Patent Analysis: Distribution of Players in North America (Region-wise)
  • Table 14.30. Patent Analysis: Distribution of Players in Europe (Region-wise)
  • Table 14.31. Patent Analysis: Distribution of Players in Asia-Pacific (Region-wise)
  • Table 14.32. Patent Analysis: Distribution by Type of Company
  • Table 14.33. Patent Analysis: Distribution by Patent Age
  • Table 14.34. Patent Analysis: Distribution by CPC Classification
  • Table 14.35. Patent Analysis: Distribution by Emerging Focus Area
  • Table 14.36. Patent Analysis: Most Active Players: Distribution by Number of Patents
  • Table 14.37. Patent Analysis: Most Active Inventors: Distribution by Number of Patents
  • Table 14.38. Patent Analysis: Benchmarking
  • Table 14.39. Patent Analysis: Patent Relative Valuation
  • Table 14.40. Patent Analysis: Distribution by Patent Citation
  • Table 14.41. Patent Analysis: Distribution by Legal Status
  • Table 14.42. Patent Analysis: Distribution by Legal Status and Geography
  • Table 14.43. Partnerships and Collaborations: Distribution by Year of Partnership
  • Table 14.44. Partnerships and Collaborations: Distribution by Type of Partnership
  • Table 14.45. Partnerships and Collaborations: Distribution by Year and Type of Partnership
  • Table 14.46. Partnerships and Collaborations: Distribution by Focus Area
  • Table 14.47. Partnerships and Collaborations: Distribution by Year of Partnership and Focus Area
  • Table 14.48. Partnerships and Collaborations: Distribution by Therapeutic Area
  • Table 14.49. Partnerships and Collaborations: Distribution by Focus Area and Therapeutic Area
  • Table 14.50. Partnerships and Collaborations: Distribution by Type of Partnership and Type of Data Handled
  • Table 14.51. Partnerships and Collaborations: Distribution by Year and Type of Software Applications
  • Table 14.52. Partnerships and Collaborations: Distribution by Geography (Continent-wise)
  • Table 14.53. Partnerships and Collaborations: Distribution by Geography (Country-wise)
  • Table 14.54. Most Active Players: Distribution by Number of Partnerships
  • Table 14.55. Funding and Investments: Distribution by Year of Funding
  • Table 14.56. Funding and Investments: Distribution of Amount Invested by Year
  • Table 14.57. Funding and Investments: Distribution of Amount Invested by Type of Funding
  • Table 14.58. Funding and Investments: Distribution of Instances and Total Amount Invested by the Type of Funding
  • Table 14.59. Funding and Investments: Distribution of Instances and Total Amount Invested by Type of Venture Capital Funding
  • Table 14.60. Funding and Investments: Distribution Instances and Geography (Continent-wise)
  • Table 14.61. Funding and Investments: Distribution of Instances and Geography (Country-wise)
  • Table 14.62. Funding and Investments: Distribution of Amount Invested by Geography
  • Table 14.63. Funding and Investments: Distribution of Instances by Year and Type of Funding
  • Table 14.64. Funding and Investments: Distribution of Instances by Therapeutic Area
  • Table 14.65. Funding and Investments: Distribution of Instances by Type of Data Handled
  • Table 14.66. Most Active Players: Distribution by Number of Funding Instances and Amount Invested
  • Table 14.67. Most Active Investors: Distribution by Number of Funding Instances
  • Table 14.68. AC Matrix: North America Scenario
  • Table 14.69. AC Matrix: Europe Scenario
  • Table 14.70. AC Matrix: Asia Pacific and RoW Scenario
  • Table 14.71. Global Precision Medicine Software Developers Market, 2021-2031 (USD Million)
  • Table 14.72. Precision Medicine Software Developers Market: Distribution by Therapeutic Area, 2021-2031 (USD Million)
  • Table 14.73. Precision Medicine Software Developers Market for Oncological Disorders, 2021-2031 (USD Million)
  • Table 14.74. Precision Medicine Software Developers Market for Cardiovascular Disorders, 2021-2031 (USD Million)
  • Table 14.75. Precision Medicine Software Developers Market for Neurological Disorders, 2021-2031 (USD Million)
  • Table 14.76. Precision Medicine Software Developers Market for Metabolic Disorders, 2021-2031 (USD Million)
  • Table 14.77. Precision Medicine Software Developers Market: Distribution by Geography, 2021-2031 (USD Million)
  • Table 14.78. Precision Medicine Software Developers Market in North America, 2021-2031 (USD Million)
  • Table 14.79. Precision Medicine Software Developers Market in Europe, 2021-2031 (USD Million)
  • Table 14.80. Precision Medicine Software Developers Market in Asia-Pacific and RoW, 2021-2031 (USD Million)
  • Table 14.81. Precision Medicine Software Developers Market: Distribution by Type of Type of End-User, 2021-2031 (USD Million)
  • Table 14.82. Precision Medicine Software Developers Market for Healthcare Providers, 2021-2031 (USD Million)
  • Table 18.83. Precision Medicine Software Developers Market for Research and Government Institutes, 2021-2031 (USD Million)
  • Table 18.84. Precision Medicine Software Developers Market for Pharmaceutical and Biotech Companies, 2021-2031 (USD Million)

List Of Companies

The following companies and organizations have been mentioned in the report.

  • 1. 2bPrecise
  • 2. 2nd.MD
  • 3. 4D Path
  • 4. 83North
  • 5. AB Enzymes
  • 6. Abu Dhabi Health Data Services
  • 7. ACE & Company
  • 8. AceTech
  • 9. Admera Health
  • 10. Advaita
  • 11. AdventHealth
  • 12. Adventist Health
  • 13. Aetna
  • 14. AG Mednet
  • 15. Agilent Technologies
  • 16. Ainnova Tech
  • 17. AIQ Solutions
  • 18. Alexandria Venture Investments
  • 19. AliveAndKickn
  • 20. Allscripts
  • 21. Ally Bridge Group
  • 22. Altis Labs
  • 23. Altium Capital
  • 24. Alychlo
  • 25. AMedSU
  • 26. American Heart Association
  • 27. American Society of Clinical Oncology
  • 28. Amgen
  • 29. AMITA Health
  • 30. aMoon
  • 31. AMRA Medical
  • 32. PathWest Laboratory Medicine
  • 33. ARCH Venture Partners
  • 34. Ariel Precision Medicine
  • 35. ARUP Laboratories
  • 36. Ascension Ventures
  • 37. Asset Management Ventures
  • 38. Astarte Medical
  • 39. AstraZeneca
  • 40. ATW Partners
  • 41. Audacy
  • 42. Australian BioCommons
  • 43. Australian Research Data Commons (ARDC)
  • 44. Axiom Associates
  • 45. Babylon Health
  • 46. Baillie Gifford
  • 47. Bain Capital Ventures
  • 48. Bainbridge Health
  • 49. Balderton Capital
  • 50. Barts Health NHS Trust
  • 51. Bayer
  • 52. BC Platforms
  • 53. Beacon Capital
  • 54. Belgian Society of Medical Oncology
  • 55. BenevolentAI
  • 56. Biocept
  • 57. BioVariance
  • 58. Blueprint Medicines
  • 59. Boehringer Ingelheim Venture Fund
  • 60. Brainomix
  • 61. Breakthrough Genomics
  • 62. Briban Invest
  • 63. Bristol Myers Squibb
  • 64. Broad Institute
  • 65. Business Development Bank of Canada
  • 66. C2i Genomics
  • 67. Caesar
  • 68. Apple
  • 69. Cancer Genetics
  • 70. CancerIQ
  • 71. Capital Midwest Fund
  • 72. Caris Life Sciences
  • 73. Casdin Capital
  • 74. Catipult.AI
  • 75. Clayton, Dubilier & Rice (CD&R)
  • 76. Celgene
  • 77. Centana Growth Partners
  • 78. CENTOGENE
  • 79. Centro Hospitalar Lisboa Ocidental
  • 80. Cergentis
  • 81. Children's Brain Tumor Tissue Consortium
  • 82. Chimera Partners
  • 83. Cigna Ventures
  • 84. Circle Cardiovascular Imaging
  • 85. Claremont Creek Ventures
  • 86. Cofactor Genomics
  • 87. Cohesic
  • 88. Colle Capital
  • 89. Color
  • 90. Community Health Network
  • 91. ConCR
  • 92. Connect Ventures
  • 93. Cornerstone Specialty Network
  • 94. Cortex
  • 95. Crohn's & Colitis Foundation
  • 96. CureMatch
  • 97. Curii
  • 98. Data4Cure
  • 99. Datavant
  • 100. Decentralized Trials & Research Alliance
  • 101. Dell Technologies
  • 102. Diagnomics
  • 103. Diagnostic Laboratory Services
  • 104. Dian Diagnostics
  • 105. Discovery Life Sciences
  • 106. DNA Compass
  • 107. DNAnexus
  • 108. Dolby Family Ventures
  • 109. DoseMe (Acquired by Tabula Rasa HealthCare)
  • 110. DrChrono
  • 111. Driehaus Capital Management
  • 112. Duquesne Family Office
  • 113. Echo Health Ventures
  • 114. Eiffel Investment
  • 115. Elekta
  • 116. Elysia Capital
  • 117. Emory Healthcare
  • 118. Endeavour Vision
  • 119. e-NIOS
  • 120. EnvoyAI
  • 121. Epic App Orchard
  • 122. EpigeneticsRx
  • 123. Esplanade Ventures
  • 124. Essen University
  • 125. Eurazeo
  • 126. European Organisation for Research and Treatment of Cancer (EORTC)
  • 127. European Specialist Investment
  • 128. EW Healthcare Partners
  • 129. Fabric Genomics
  • 130. Famille C Invest
  • 131. Farsight Genome Systems
  • 132. Feist-Weiller Cancer Center
  • 133. First Round Capital
  • 134. Flatiron Health
  • 135. Fluidigm
  • 136. Flywheel
  • 137. Foresite Capital
  • 138. Foundation Medicine
  • 139. F-Prime Capital
  • 140. Franklin Templeton
  • 141. Friends of Cancer Research
  • 142. GE Healthcare
  • 143. Geisinger
  • 144. Genedata
  • 145. General Catalyst
  • 146. Generation Investment Management
  • 147. Genetic Alliance
  • 148. Genetic Technologies
  • 149. GeneXplain
  • 150. Genmab
  • 151. Genome Medical
  • 152. GenomOncology
  • 153. Genomelink
  • 154. Genomenon
  • 155. Genomics England
  • 156. Genomind
  • 157. GenomOncology
  • 158. GenomSys
  • 159. Genospace
  • 160. GenXys Health Care Systems
  • 161. Gilead Sciences
  • 162. GNS Healthcare
  • 163. Golden Helix
  • 164. Green Shield Canada
  • 165. GreenM
  • 166. GV
  • 167. Hamilton Health Sciences
  • 168. Healix
  • 169. Health Catalyst Capital
  • 170. Health Innovation Manchester
  • 171. Healthgen AI
  • 172. HealthQuad
  • 173. Hearst Health
  • 174. Heritas Capital
  • 175. Highmark Health
  • 176. Hitachi
  • 177. Hôpital Foch
  • 178. Houston Methodist
  • 179. Huami
  • 180. HudsonAlpha Institute
  • 181. Human Longevity
  • 182. Hygea Precision Medicine
  • 183. Hyperfine
  • 184. Ibex Medical Analytics
  • 185. IBM
  • 186. International Development Association (IDA)
  • 187. Idinvest Partners
  • 188. iGlobe Partners
  • 189. Illumina
  • 190. Illumina Ventures
  • 191. Imaging Biometrics
  • 192. Imaginostics
  • 193. ImmunityBio
  • 194. Indiana Clinical and Translational Sciences Institute
  • 195. Indiana University
  • 196. Industrifonden
  • 197. iNDX.Ai
  • 198. InformedDNA
  • 199. Innovatus Capital Partners
  • 200. Inova Health System
  • 201. InsightRX
  • 202. Inspirata
  • 203. Integrated DNA Technologies
  • 204. Intellihealth
  • 205. Interactive Biosoftware
  • 206. Intermountain Healthcare
  • 207. Intero Life Sciences
  • 208. Intertrust Technologies
  • 209. IntrinsiQ Specialty Solutions
  • 210. IQVIA
  • 211. IRA Capital
  • 212. Janssen
  • 213. JDRF
  • 214. JiNan Danjier
  • 215. Kamet Ventures
  • 216. Kinship
  • 217. Koninklijke Philips
  • 218. Konyang University Hospital
  • 219. Kura Oncology
  • 220. LabCorp
  • 221. Lifebit
  • 222. LifeOmic Health
  • 223. Livongo
  • 224. LSS
  • 225. LunaPBC
  • 226. M2Gen
  • 227. MacroGenics
  • 228. Marienhaus Hospital
  • 229. Mary Crowley Cancer Research
  • 230. Mayo Clinic
  • 231. McKesson Ventures
  • 232. medASTUTE
  • 233. Medfusion
  • 234. Medical University of South Carolina
  • 235. Medidata
  • 236. MedImpact
  • 237. Medimsight
  • 238. Medipredict
  • 239. Medley Genomics
  • 240. Merck
  • 241. Merck Global Health Innovation Fund
  • 242. Merstal
  • 243. Merus
  • 244. Metabolon
  • 245. Microsoft
  • 246. MidCap Financial
  • 247. MindX Sciences
  • 248. Mission Bio
  • 249. Moffitt Cancer Center
  • 250. Molecular Health
  • 251. MolecularMatch
  • 252. MTIP
  • 253. Multiple Myeloma Research Foundation
  • 254. Murfreesboro Medical Clinic & SurgiCenter
  • 255. mymo.AI
  • 256. Myriad Genetics
  • 257. NantHealth
  • 258. NantOmics
  • 259. Nashville Veterans Affairs Hospital
  • 260. Natera
  • 261. National Cancer Center
  • 262. National Cancer Institute
  • 263. National Institute of Health
  • 264. NeoGenomics
  • 265. New Enterprise Associates
  • 266. Nextrans
  • 267. NFX
  • 268. NHS
  • 269. National Instruments (NI)
  • 270. National Institutes of Health (NIH)
  • 271. Nimbus Synergies
  • 272. Northpond Ventures
  • 273. NorthShore University HealthSystem
  • 274. Northwell Health
  • 275. Northwest Firefighters Benefits Trust
  • 276. Notable
  • 277. Novartis
  • 278. Novo Holdings
  • 279. NovogeneAIT Genomics
  • 280. NYU Grossman School of Medicine
  • 281. Octopus Ventures
  • 282. Ohio State University
  • 283. Olea Medical
  • 284. Oncora Medical
  • 285. OncXerna Therapeutics
  • 286. OneOncology
  • 287. Oracle
  • 288. Orion Health
  • 289. Osage University Partners
  • 290. Outcomes4Me
  • 291. Oxford University
  • 292. Pancreatic Cancer Action Network
  • 293. Paragon Genomics
  • 294. Parexel
  • 295. Parkwalk Advisors
  • 296. Pentech Ventures
  • 297. Perceiv AI
  • 298. Perceptive Advisors
  • 299. Personal Genome Diagnostics
  • 300. Pfizer
  • 301. Pharmatics
  • 302. PhenoTips®
  • 303. Phillips
  • 304. Phosphorus
  • 305. PierianDx
  • 306. Pillar Biosciences
  • 307. Pinnacle
  • 308. PipelineRx
  • 309. Planven Entrepreneur Ventures
  • 310. Precision Digital Health
  • 311. Precision for Medicine
  • 312. Precision Health Informatics
  • 313. Precision Health Software
  • 314. Premier
  • 315. Preon Capital
  • 316. Prisma Health
  • 317. Proscia
  • 318. Prudential Financial
  • 319. Psyche Systems
  • 320. Psychiatry-UK
  • 321. Pygar
  • 322. Q2 Solutions
  • 323. QIAGEN
  • 324. Qlucore
  • 325. QMENTA
  • 326. QNA Dx
  • 327. Quadria Capital
  • 328. Quantgene
  • 329. QUBIS
  • 330. Quest Diagnostics
  • 331. Qynapse
  • 332. Renalytix AI
  • 333. Renown Health
  • 334. RetInSight
  • 335. Revelation Alpine
  • 336. Revolution Growth
  • 337. Roche
  • 338. Rock River Capital Partners
  • 339. 30Ventures
  • 340. RTI International
  • 341. Russell Microcap Index
  • 342. RxGenomix
  • 343. RXVIP Concierge
  • 344. Safeguard Scientifics
  • 345. San Francisco Otolaryngology
  • 346. Sanford Health
  • 347. Sano Genetics
  • 348. Sanofi
  • 349. SAP
  • 350. SCA Robotics
  • 351. ScienceVision
  • 352. ScreenPoint Medical
  • 353. Section 32
  • 354. Sentieon
  • 355. Seoul National University Hospital
  • 356. Sequoia
  • 357. Seven Bridges
  • 358. Sidney Kimmel Cancer Center
  • 359. Siemens Healthineers
  • 360. Sierra Ventures
  • 361. SimplicityBio
  • 362. SJF Ventures
  • 363. Social Capital
  • 364. SocialGenomics
  • 365. Sonraí Analytics
  • 366. SOPHiA GENETICS
  • 367. Spanish Lung Cancer
  • 368. St. Joseph's/Candler
  • 369. St. Jude Children's Research Hospital
  • 370. Stanford Health Care
  • 371. Stone Checker
  • 372. Strand Life Sciences
  • 373. Stryker
  • 374. Studio Management
  • 375. Sun Life
  • 376. Sunquest Information Systems
  • 377. Susman Ventures
  • 378. Sutter Health
  • 379. Swisscom Ventures
  • 380. Syapse
  • 381. T. Rowe Price
  • 382. Tabula Rasa HealthCare
  • 383. Takeda
  • 384. Taliaz
  • 385. Teamsters
  • 386. TeamViewer
  • 387. Techstart Ventures
  • 388. Teladoc Health
  • 389. TELUS Ventures
  • 390. Tempus Labs
  • 391. Ten Coves Capital
  • 392. TeraRecon
  • 393. Terumo
  • 394. The Mark Foundation for Cancer Research
  • 395. Parker Institute
  • 396. Thermo Fisher Scientific
  • 397. Thomas Jefferson University
  • 398. TIGAR Health Technologies
  • 399. Tiger Global Management
  • 400. Tiny VC
  • 401. Tmunity Therapeutics
  • 402. Topcon Healthcare
  • 403. TPG Biotech
  • 404. Translational Sciences Institute
  • 405. Translational Software
  • 406. Trapelo Health
  • 407. Trialbee
  • 408. TriCore Reference Laboratories
  • 409. Triesta Sciences
  • 410. TwinStrand Biosciences
  • 411. Twist Bioscience
  • 412. Tydo
  • 413. UK Research and Innovation
  • 414. uMETHOD
  • 415. UnitedHealthcare
  • 416. University Hospital of Augsburg
  • 417. University of California
  • 418. University of Chicago
  • 419. University of Missouri Health Care
  • 420. University of Pittsburgh Medical Center (UPMC)
  • 421. US Orthopedic Alliance
  • 422. Vanderbilt-Ingram Cancer Center
  • 423. Vanderbilt University Medical Center
  • 424. Varian
  • 425. Verily Life Sciences
  • 426. Vicinity
  • 427. Vidence
  • 428. VigiLanz
  • 429. Viking Global Investors
  • 430. Visiopharm
  • 431. Welfare Fund of Philadelphia
  • 432. Wellcome Sanger Institute
  • 433. Wisconsin Investment Partners
  • 434. Genuity Science (formerly known as WuXi NextCODE)
  • 435. XIFIN
  • 436. Y Combinator
  • 437. YouScript
  • 438. Zero Childhood Cancer
  • 439. ZS Associates
目次

Title:
Precision Medicine Software Developers
Market by Target Therapeutic Indication (Oncological Disorders, Cardiovascular Disorders, Neurological Disorders, Metabolic Disorders), Key Geographical Regions (North America, Europe, Asia-Pacific) and Types of End Users (Healthcare Providers, Research and Government Institutes, Pharmaceutical and Biotech Companies): Industry Trends and Global Forecasts, 2021-2031.

Example Insights:

Overview

Various studies have indicated that the genetic composition of two individuals is unlikely to be similar. This can be attributed to the fact that the genetic makeup of an individual is influenced by various factors, such as family history, as well as environmental and health conditions. Therefore, one treatment cannot be expected to be successful in every patient suffering from the same disorder. It is worth highlighting that the inability to report a health issue to a medical practitioner in its initial stage is expected to cost productivity losses worth over USD 40-90 billion, each year. Further, frequent hospitals visits can cause additional financial burden on patients. In order to mitigate the aforementioned challenges, healthcare professionals are shifting towards the use of personalized / precision medicine. This approach, as opposed to the one-size-fits-all approach, enables healthcare professionals to offer a precise treatment option for a specific disease that is likely to prove effective for a group of individuals. This domain has the ability to reduce treatment burden across many therapeutic areas including oncological disorders, rheumatology disorders.

Given the various advantages offered by precision medicine, healthcare organizations are gradually becoming more interested in adopting such solutions. Further, with the advent of bioinformatics and artificial intelligence tools, there has been a significant rise in the adoption of such applications. For instance, in June 2020, Infosys launched its proprietary personalized medicine solution, equipped with latest SAP S/4HANA® technology, to gain intelligent insights to deliver personalized experience to patients. It is worth highlighting that precision medicine software solutions are widely used by healthcare providers for the diagnosis, as well as prognosis, of the disease. However, the scope is being continuously expanded in order to include the prevention and recovery of life threatening diseases. At present, several software applications integrate clinical and diagnostic data, along with financial data, offering deeper and precise insights to healthcare providers, as well as helping them improve patient outcomes. Players engaged in the development of precision medicine software applications have observed a significant growth over the past few years. More than 120 software solutions have been developed and are available commercially. It is also worth highlighting that over USD 2 billion has been invested in this domain by various stakeholders in the last four years. As a result of the rising adoption and preference for precision medicine software applications, coupled to the ongoing efforts of software providers to further improve the current software solutions, we believe that the precision medicine software services market is likely to witness significant growth in the foreseen future.

Scope of the Report

The "Precision Medicine Software Developers Market by Target Therapeutic Indication (Oncological Disorders, Cardiovascular Disorders, Neurological Disorders, Metabolic Disorders), Key Geographical Regions (North America, Europe, Asia-Pacific) and Types of End Users (Healthcare Providers, Research and Government Institutes, Pharmaceutical and Biotech Companies): Industry Trends and Global Forecasts, 2021-2031" report features an extensive study of the current landscape, offering an informed opinion on the likely adoption of precision medicine software in the healthcare industry, over the next decade. The report features an in-depth analysis, highlighting the capabilities of various stakeholders engaged in this domain. Amongst other elements, the report features the following:

  • A detailed overview of the current market landscape of precision medicine software developers, along with information on several relevant parameters, such as year of establishment, company size, location of headquarters, types of platforms (cloud-based and on-premises) , purpose of software (diagnosis, analysis, treatment) , type of data (genomic data, clinical data, image data and others) , therapeutic area (oncological disorders, cardiovascular disorders, neurological disorders, metabolic disorders) and types of end users (healthcare providers, research and government institutes, pharmaceutical and biotech companies) .
  • Elaborate profiles of key players engaged in the development of precision medicine software applications. Each profile features a brief overview of the company, along with its information on technology / service portfolio, recent developments and an informed future outlook.
  • A detailed analysis of the various patents that have been filed / granted within this domain, since 2018. It highlights the key trends associated with these patents across several relevant parameters, such as publication year, geographical location / patent jurisdiction, CPC symbols, emerging focus areas, type of organization, leading patent assignees and most active players (in terms of number of patents filed) . In addition, it includes a patent benchmarking analysis and patent valuation.
  • An analysis of the recent partnerships inked between various players engaged in this domain, during the period 2018-2021, based on several relevant parameters, such as year of partnership, type of partnership model adopted, regional distribution (continent and country-wise) and most active players (in terms of number of partnerships inked).
  • A detailed analysis of various investments made by players engaged in this domain, based on several relevant parameters such as year of investment, number of funding instances, amount invested and type of funding (venture capital financing, debt financing, grants / awards, initial public offering (IPO) ) undertaken by companies engaged in this domain, during the period 2018-2021.
  • A detailed analysis based on a proprietary 2x2 representation, highlighting the current market scenario (in terms of existing competition and growth opportunities) across emerging and established market segments.
  • A detailed discussion on affiliated trends, key drivers and challenges, under a SWOT framework, which are likely to impact the industry's evolution, along with a Harvey ball analysis.

One of the key objectives of the report was to estimate the existing market size and future potential of precision medicine software developers, over the coming decade. Further, we have provided an informed estimate of the market's evolution, during the period 2021-2031, based on several relevant parameters, such as adoption trends, and expected price variations for these products. The report features the likely distribution of the current and forecasted opportunity within the precision medicine software market across [A] Therapeutic Indication (Oncological Disorders, Cardiovascular Disorders, Neurological Disorders, Metabolic Disorders), [B] Key Geographical Regions (North America, Europe, Asia-Pacific) , [C] Types of End Users (Healthcare Providers, Research and Government Institutes, Pharmaceutical and Biotech Companies) .

All actual figures have been sourced and analyzed from publicly available information forums and secondary research discussions. Financial figures mentioned in this report are in USD, unless otherwise specified.

Key Questions Answered:

  • Who are the key players engaged in the development of precision medicine software applications?
  • Which type of platform is more likely to outreach the market in the near future?
  • Which companies are actively engaged in the development of precision medicine software applications?
  • What are the major therapeutic areas targeted by various precision medicine software applications?
  • What kind of partnership models are commonly adopted by industry stakeholders?
  • Who are the key investors in this domain?
  • Who are the target users of precision medicine software applications?
  • What are the different types of data being handled by precision medicine software developers?
  • What is the main purpose for using precision medicine software applications?
  • How is the current and future opportunity likely to be distributed across key market segments?

Chapter Outlines:

Chapter 2 is an executive summary of key insights captured in our research. It offers a high-level view on the current state of precision medicine software market and its likely evolution in the mid to long term.

Chapter 3 provides a general introduction to precision medicine and precision medicine software solutions and its historical evolution. It further includes a brief outline on the need for software solutions, along with information on the various patient monitoring related services offered by players engaged in this domain. Furthermore, it highlights prevalent advantages and key challenges associated with precision medicine software, featuring details related to the current and future trends in the domain.

Chapter 4 provides a detailed overview of the overall market landscape of players engaged in providing precision medicine software solutions, along with information on several relevant parameters, such as year of establishment, company size, location of headquarters, types of platforms (cloud-based, on-premises), purpose of software (diagnosis, analysis, treatment), type of data handled (genomic data, clinical data, image data, omics data), therapeutic area (oncological disorders, cardiovascular disorders, neurological disorders, metabolic disorders), types of end users (healthcare providers, research and government institutes, pharmaceutical and biotech companies).

Chapter 5 includes detailed profiles of the key players that are active in this domain. Each profile includes a brief overview of the company, its information on technology / service portfolio, recent developments and an informed future outlook.

Chapter 6 features a comprehensive company competitiveness analysis, highlighting prominent players among two peer groups (North America and Europe and Asia Pacific) that we came across during our research. The chapter provides a comparative analysis of the companies within each peer group on the basis of supplier strength (considering a company's overall experience in the industry).

Chapter 7 provides an overview of the various patents related to precision medicine software solutions that have been filed / granted, since 2018. It highlights the key trends associated with these patents across various parameters, such as patent publication year, geographical location / patent jurisdiction, CPC symbols, emerging focus areas, type of organization, leading patent assignees and the leading players (in terms of number of patents filed). In addition, it includes a patent benchmarking analysis and a detailed valuation analysis.

Chapter 8 features an analysis of the recent partnerships inked between precision medicine software developers, during the period 2018-2021 Additionally, it includes a brief description of the various types of partnerships models (such as product / software integration agreement, service alliance, service agreement, product / software development agreement, full business acquisition, product / software distribution agreement, product / software utilization agreement, and product portfolio acquisition) that have been adopted by stakeholders engaged in this domain, during the period 2018-2021.

Chapter 9 provides an analysis of various investments made by players engaged in this domain based on several relevant parameters, such as year of investment, number of funding instances, amount invested and type of funding (such as, venture capital, private equity, secondary offerings, debt, initial public offering (IPO), other equity, seed, grant, and others), along with information on the most active players (in terms of number of funding instances and amount raised) and most active investors (in terms of number of funding instances).

Chapter 10 features a proprietary 2x2 representation, highlighting the current market scenario (in terms of existing competition and growth opportunities) across emerging and established market segments.

Chapter 11 features a detailed market forecast analysis, highlighting the likely evolution of the market in the short to mid-term and long term, for the period 2021-2031. Additionally, the report features the likely distribution of the current and forecasted opportunity across [A] target therapeutic area (oncological disorders, cardiovascular disorders, neurological disorders, metabolic disorders), [B] key geographical regions (North America, Europe, Asia-Pacific) and [C] end user (healthcare providers, research & government institutes, pharmaceutical & biotech companies).

Chapter 12 provides a detailed discussion on affiliated trends, key drivers and challenges, under a SWOT framework, which are likely to impact the industry's evolution, along with a Harvey ball analysis, highlighting the relative effect of each SWOT parameter on the overall precision medicine software developers.

Chapter 13 is a summary of the entire report. In this chapter, we have provided a list of key takeaways from the report, and expressed our independent opinion related to the research and analysis described in the previous chapters.

Chapter 14 is an appendix, which provides tabulated data and numbers for all the figures included in the report.

Chapter 15 is an appendix, which contains the list of companies and organizations mentioned in the report.

TABLE OF CONTENTS

1. PREFACE

  • 1.1. Scope of the Report
  • 1.2. Research Methodology
  • 1.3. Key Questions Answered
  • 1.4. Chapter Outlines

2. EXECUTIVE SUMMARY

  • 2.1. Chapter Overview

3. INTRODUCTION

  • 3.1. Chapter Overview
  • 3.2. Overview of Precision Medicine
    • 3.2.1. Evolution of Precision Medicine
    • 3.2.2. Novel Approaches in Precision Medicine
      • 3.2.2.1 Biomarkers
        • 3.2.2.1.1. Biomarkers and Decision Making
        • 3.2.2.1.2. Genomics, Epigenetics and MicroRNAs as Emerging Biomarkers
        • 3.2.2.1.3 Biomarker Multiplexing
        • 3.2.2.1.4. Digital Biomarkers
      • 3.2.2.2. Metabolomics
  • 3.3. Key Technology Platforms
    • 3.3.1. Cloud Based
    • 3.3.2. On-Premises
  • 3.4. Key Challenges Faced by Precision Medicine Software Developers
    • 3.4.1. Unprecedented Data Volumes
    • 3.4.2. Interpreting Data Deluge at Individual Level
    • 3.4.3. Incorporation of Solutions in the Clinic
  • 3.5. Application Areas
    • 3.5.1. Therapeutic Areas
      • 3.5.1.1. Oncological Disorders
      • 3.5.1.2. Cardiovascular Disorders
      • 3.5.1.3. Respiratory Disorders
      • 3.5.1.4. Rare Disorders
    • 3.5.2. Pharmacogenomics
      • 3.5.2.1. Genetic Variations
      • 3.5.2.2. Drug Development
  • 3.6. Benefits of Precision Medicine over Traditional Treatment Modalities
    • 3.6.1. Benefits to Patients
    • 3.6.2. Benefits to Healthcare Providers
  • 3.7. Future Perspectives

4. MARKET LANDSCAPE

  • 4.1. Chapter Overview
  • 4.2. Precision Medicine Software Developers: Overall Market Landscape
    • 4.2.1. Analysis by Year of Establishment
    • 4.2.2. Analysis by Company Size
    • 4.2.3. Analysis by Region
    • 4.2.4. Analysis by Type of Platform
    • 4.2.5. Analysis by Purpose of Software Applications
    • 4.2.6. Analysis by Type of Data Handled
    • 4.2.7. Analysis by Therapeutic Area
    • 4.2.8. Analysis by Type of End User
  • 4.3. Key Insights

5. COMPANY PROFILES

  • 5.1. Chapter Overview
  • 5.2. Precision Medicine Software Developers
    • 5.2.1. Ariel Precision Medicine
      • 5.2.1.1. Company Overview
      • 5.2.1.2. Product Portfolio
      • 5.2.1.3. Recent Developments and Future Outlook
    • 5.2.2. C2i Genomics
      • 5.2.2.1. Company Overview
      • 5.2.2.2. Product Portfolio
      • 5.2.2.3. Recent Developments and Future Outlook
    • 5.2.3. Genedata
      • 5.2.3.1. Company Overview
      • 5.2.3.2. Product Portfolio
      • 5.2.3.3. Recent Developments and Future Outlook
    • 5.2.4. Inspirata
      • 5.2.4.1. Company Overview
      • 5.2.4.2. Product Portfolio
      • 5.2.4.3. Recent Developments and Future Outlook
    • 5.2.5. IQVIA
      • 5.2.5.1. Company Overview
      • 5.2.5.2. Product Portfolio
      • 5.2.5.3. Recent Developments and Future Outlook
    • 5.2.6. SAP
      • 5.2.6.1. Company Overview
      • 5.2.6.2. Product Portfolio
      • 5.2.6.3. Recent Developments and Future Outlook
  • 5.3. Additional Profiles
    • 5.3.1. Fabric Genomics
      • 5.3.1.1. Company Overview
      • 5.3.1.2. Product Portfolio
      • 5.3.1.3. Recent Developments and Future Outlook
    • 5.3.2. GenomOncology
      • 5.3.2.1. Company Overview
      • 5.3.2.2. Product Portfolio
      • 5.3.2.3. Recent Developments and Future Outlook
    • 5.3.3. Human Longevity
      • 5.3.3.1. Company Overview
      • 5.3.3.2. Product Portfolio
      • 5.3.3.3. Recent Developments and Future Outlook
    • 5.3.4. SOPHiA GENETICS
      • 5.3.4.1. Company Overview
      • 5.3.4.2. Product Portfolio
      • 5.3.4.3. Recent Developments and Future Outlook
    • 5.3.5. Syapse
      • 5.3.5.1. Company Overview
      • 5.3.5.2. Product Portfolio
      • 5.3.5.3. Recent Developments and Future Outlook

6. COMPANY COMPETITIVENESS ANALYSIS

  • 6.1. Chapter Overview
  • 6.2. Key Parameters
  • 6.3. Methodology
  • 6.4. Company Competitiveness Analysis: Precision Medicine Software Developers
    • 6.4.1. Company Competitiveness Analysis: Large and Very Large Companies
    • 6.4.2. Company Competitiveness Analysis: Mid-sized Companies
    • 6.4.3. Company Competitiveness Analysis: Small Companies

7. PATENT ANALYSIS

  • 7.1. Chapter Overview
  • 7.2. Scope and Methodology
  • 7.3. Precision Medicine Software Developers: Patent Analysis
    • 7.3.1. Analysis by Type of Patent
    • 7.3.2. Analysis by Publication Year
    • 7.3.4. Analysis by Publication Year and Granted Patents
    • 7.3.5. Analysis by Geography (Continent-wise)
    • 7.3.6. Analysis by Region (Country-wise)
    • 7.3.7. Analysis by Type of Company
      • 7.3.7.1 Industry Players
      • 7.3.7.2 Non-Industry Players
    • 7.3.8. Analysis by Patent Age
    • 7.3.9. Analysis by CPC Classification
    • 7.3.10. Analysis by Emerging Focus Area
    • 7.3.11. Most Active Players: Analysis by Number of Patents
    • 7.3.12. Most Active Inventors: Analysis by Number of Patents
    • 7.3.13. Patent Benchmarking Analysis
    • 7.3.14. Patent Valuation Analysis
    • 7.3.15. Analysis by Citation
    • 7.3.16. Analysis by Type of Legal Status
      • 7.3.16.1. Analysis by Legal Status
      • 7.3.16.2. Analysis by Geography and Legal Status

8. PARTNERSHIPS AND COLLABORATIONS

  • 8.1. Chapter Overview
  • 8.2. Partnership Models
  • 8.3. Precision Medicine Software Developers: Recent Partnerships and Collaborations
    • 8.3.1. Analysis by Year of Partnership
    • 8.3.2. Analysis by Type of Partnership
    • 8.3.3. Analysis by Year and Type of Partnership
    • 8.3.4. Analysis by Focus Area
    • 8.3.5. Analysis by Year of Partnership and Focus Area
    • 8.3.6. Analysis by Type of Partnership and Focus Area
    • 8.3.7. Analysis by Therapeutic Area
    • 8.3.8. Analysis by Type of Partnership and Type of Platform
    • 8.3.9. Analysis by Type of Partnership and Type of Data Handled
    • 8.3.10. Analysis by Region
      • 8.3.10.1. Continent-wise Distribution
      • 8.3.10.2. Intercontinental and Intracontinental Distribution
      • 8.3.10.3. Country-wise Distribution
    • 8.3.11. Most Active Players: Analysis by Number of Partnerships

9. FUNDING AND INVESTMENT ANALYSIS

  • 9.1. Chapter Overview
  • 9.2. Types of Funding
  • 9.3. Precision Medicine Software Developers: Funding and Investment Analysis
    • 9.3.1 Analysis by Year, Type of Funding and Amount Invested
    • 9.3.2. Analysis of Instances by Year
    • 9.3.3. Analysis of Amount Invested by Year
    • 9.3.4. Analysis of Amount Invested by Type of Funding
      • 9.3.4.1. Analysis of Instances and Total Amount Invested by Type of Funding
      • 9.3.4.2. Analysis of Instances and Total Amount Invested by Type of Venture Capital Funding
    • 9.3.5. Analysis by Geography
      • 9.3.5.1. Continent-wise Distribution
      • 9.3.5.2. Country-wise Distribution
    • 9.3.6. Analysis of Amount Invested by Geography
    • 9.3.7. Analysis of Instances by Year and Type of Funding
    • 9.3.8. Analysis of Instances by Type of Investor
    • 9.3.9. Analysis of Instances by Purpose of Funding
    • 9.3.10. Analysis of Instances by Therapeutic Area
    • 9.3.11. Analysis of Instances by Type of Data Handled
    • 9.3.12. Most Active Players: Analysis by Number of Funding Instances and Amount Invested
    • 9.3.13. Key Investors: Analysis by Number of Instances
    • 9.3.14. Funding and Investment Summary

10. ATTRACTIVENESS COMPETETIVENESS MATRIX

  • 10.1. Chapter Overview
  • 10.2. AC Matrix: Overview
    • 10.2.1. Strong Business Segments
    • 10.2.2. Average Business Segments
    • 10.2.3. Weak Business Segments

11. MARKET FORECAST

  • 11.1. Chapter Overview
  • 11.2. Forecast Methodology and Assumptions
  • 11.3. Global Precision Medicine Software Developers Market, 2021-2031
  • 11.4. Precision Medicine Software Developers Market, 2021-2031: Analysis by Therapeutic Area
    • 11.4.1. Precision Medicine Software Developers Market for Oncological Disorders, 2021-2031
    • 11.4.2. Precision Medicine Software Developers Market for Cardiovascular Disorders, 2021-2031
    • 11.4.3. Precision Medicine Software Developers Market for Neurological Disorders, 2021-2031
    • 11.4.4. Precision Medicine Software Developers Market for Metabolic Disorders, 2021-2031
  • 11.5. Precision Medicine Software Developers Market, 2021-2031: Analysis by Geography
    • 11.5.1. Precision Medicine Software Developers Market in North America, 2021-2031
    • 11.5.2. Precision Medicine Software Developers Market in Europe, 2021-2031
    • 11.5.3. Precision Medicine Software Developers Market in Asia-Pacific, 2021-2031
  • 11.6. Precision Medicine Software Developers Market, 2021-2031: Analysis by Type of End User
    • 11.6.1. Precision Medicine Software Developers Market for Healthcare Providers, 2021-2031
    • 11.6.2. Precision Medicine Software Developers Market for Researchers and Government Institutes, 2021-2031
    • 11.6.3. Precision Medicine Software Developers Market for Pharmaceutical and Biotech Companies, 2021-2031

12. SWOT ANALYSIS

  • 12.1. Chapter Overview
  • 12.2. Strengths
  • 12.3. Weaknesses
  • 12.4. Opportunities
  • 12.5. Threats
  • 12.6. Comparison of SWOT Factors
  • 12.7. Concluding Remarks

13. CONCLUDING REMARKS

14. APPENDIX I: TABULATED DATA

15. APPENDIX II: LIST OF COMPANIES

List Of Figures

  • Figure 2.1 Executive Summary: Developer Landscape
  • Figure 2.2 Executive Summary: Market Overview
  • Figure 2.3 Executive Summary: Partnerships and Collaborations
  • Figure 2.4 Executive Summary: Funding and Investments
  • Figure 2.5 Executive Summary: Patent Analysis
  • Figure 2.6 Executive Summary: Market Forecast
  • Figure 3.1. Evolution of Precision Medicine
  • Figure 4.1. Precision Medicine Software Developers: Distribution by Year of Establishment
  • Figure 4.2. Precision Medicine Software Developers: Distribution by Company Size
  • Figure 4.3. Precision Medicine Software Developers: Distribution by Region
  • Figure 4.4. Precision Medicine Software Developers: Distribution by Location of Headquarters
  • Figure 4.5. Precision Medicine Software Developers: Distribution by Company Size and Region
  • Figure 4.6. Precision Medicine Software Developers: Distribution by Year of Establishment, Company Size and Region
  • Figure 4.7. Precision Medicine Software Applications: Distribution by Type of Platform
  • Figure 4.8. Precision Medicine Software Applications: Distribution by Purpose of Software Applications
  • Figure 4.9. Precision Medicine Software Applications: Distribution by Type of Data Handled
  • Figure 4.10. Precision Medicine Software Applications: Distribution by Therapeutic Area
  • Figure 4.11. Precision Medicine Software Applications: Distribution by Type of Data Handled and Therapeutic Area
  • Figure 4.12. Precision Medicine Software Applications: Distribution by Regulatory Accreditation Received
  • Figure 4.13. Precision Medicine Software Applications: Distribution by Status of Software Applications
  • Figure 4.14. Precision Medicine Software Applications: Distribution by Status of Software Applications and Region
  • Figure 4.15. Precision Medicine Software Applications: Distribution by Therapeutic Area and Status of Software Applications
  • Figure 4.16. Precision Medicine Software Applications: Distribution by Type of Data Handled and Status of Software Applications
  • Figure 4.17. Precision Medicine Software Applications: Distribution by Type of End-User
  • Figure 4.18. Precision Medicine Software Developers: Most Active Players, Distribution by Number of Software Applications
  • Figure 6.1. Company Competitiveness: Small Companies
  • Figure 6.2. Company Competitiveness: Mid-sized Companies
  • Figure 6.3. Company Competitiveness: Large and Very Large Companies
  • Figure 6.4. Company Competitiveness: Companies in North America
  • Figure 6.5. Company Competitiveness: Companies in Europe, Asia-Pacific and RoW
  • Figure 6.6. Company Competitiveness: Most Active Players
  • Figure 7.1. Patent Analysis: Distribution by Type of Patent
  • Figure 7.2. Patent Analysis: Distribution by Publication Year
  • Figure 7.3. Patent Analysis: Distribution of Granted Patents by Publication Year
  • Figure 7.4. Patent Analysis: Distribution by Geography (Continent-wise)
  • Figure 7.5. Patent Analysis: Distribution of Players in North America (Region-wise)
  • Figure 7.6. Patent Analysis: Distribution of Players in Europe (Region-wise)
  • Figure 7.7. Patent Analysis: Distribution of Players in Asia-Pacific (Region-wise)
  • Figure 7.8. Patent Analysis: Distribution by Type of Company
  • Figure 7.9. Patent Analysis: Distribution by Patent Age
  • Figure 7.10. Patent Analysis: Distribution by CPC Classification
  • Figure 7.11. Patent Analysis: Distribution by Emerging Focus Area
  • Figure 7.12. Most Active Players: Distribution by Number of Patents
  • Figure 7.13. Most Active Inventors: Distribution by Number of Patents
  • Figure 7.14. Patent Analysis: Benchmarking
  • Figure 7.15. Patent Analysis: Patent Relative Valuation
  • Figure 7.16. Patent Analysis: Distribution by Patent Citation
  • Figure 7.17. Patent Analysis: Distribution by Legal Status
  • Figure 7.18. Patent Analysis: Distribution by Legal Status and Geography
  • Figure 8.1. Partnerships and Collaborations: Distribution by Year of Partnership
  • Figure 8.2. Partnerships and Collaborations: Distribution by Type of Partnership
  • Figure 8.3. Partnerships and Collaborations: Distribution by Year and Type of Partnership
  • Figure 8.4. Partnerships and Collaborations: Distribution by Focus Area
  • Figure 8.5. Partnerships and Collaborations: Distribution by Year of Partnership and Focus
  • Figure 8.6. Partnerships and Collaborations: Distribution by Therapeutic Area
  • Figure 8.7. Partnerships and Collaborations: Distribution by Focus Area and Therapeutic Area
  • Figure 8.8. Partnerships and Collaborations: Distribution by Type of Partnership and Type of Data Handled
  • Figure 8.9. Partnerships and Collaborations: Distribution by Year and Type of Software Applications
  • Figure 8.10. Partnerships and Collaborations: Distribution by Geography (Continent-wise)
  • Figure 8.11. Partnerships and Collaborations: Distribution by Geography (Country-wise)
  • Figure 8.12. Most Active Players: Distribution by Number of Partnerships
  • Figure 9.1. Funding and Investments: Distribution by Year of Funding
  • Figure 9.2. Funding and Investments: Distribution of Amount Invested by Year
  • Figure 9.3. Funding and Investments: Distribution of Amount Invested by Type of Funding
  • Figure 9.4. Funding and Investments: Distribution of Instances and Total Amount Invested by Type of Funding
  • Figure 9.5. Funding and Investments: Distribution of Instances and Total Amount Invested by Type of Venture Capital Funding
  • Figure 9.6. Funding and Investments: Distribution of Instances and Geography (Continent-wise)
  • Figure 9.7. Funding and Investments: Distribution of Instances and Geography (Country-wise)
  • Figure 9.8. Funding and Investments: Distribution of Amount Invested by Geography
  • Figure 9.9. Funding and Investments: Distribution of Instances by Year and Type of Funding
  • Figure 9.10. Funding and Investments: Distribution of Instances by Therapeutic Area
  • Figure 9.11. Funding and Investments: Distribution of Instances by Type of Data Handled
  • Figure 9.12. Most Active Players: Distribution by Number of Funding Instances and Amount Invested
  • Figure 9.13. Most Active Investors: Distribution by Number of Funding Instances
  • Figure 10.1. AC Matrix: North America Scenario
  • Figure 10.2. AC Matrix: Europe Scenario
  • Figure 10.3. AC Matrix: Asia Pacific and RoW Scenario
  • Figure 11.1. Global Precision Medicine Software Developers Market, 2021-2031 (USD Million)
  • Figure 11.2. Precision Medicine Software Developers Market: Distribution by Therapeutic Area, 2021-2031 (USD Million)
  • Figure 11.3. Precision Medicine Software Developers Market for Oncological Disorders, 2021-2031 (USD Million)
  • Figure 11.4. Precision Medicine Software Developers Market for Cardiovascular Disorders, 2021-2031 (USD Million)
  • Figure 11.5. Precision Medicine Software Developers Market for Neurological Disorders, 2021-2031 (USD Million)
  • Figure 11.6. Precision Medicine Software Developers Market for Metabolic Disorders, 2021-2031 (USD Million)
  • Figure 11.7. Precision Medicine Software Developers Market: Distribution by Geography, 2021-2031 (USD Million)
  • Figure 11.8. Precision Medicine Software Developers Market in North America, 2021-2031 (USD Million)
  • Figure 11.9. Precision Medicine Software Developers Market in Europe, 2021-2031 (USD Million)
  • Figure 11.10. Precision Medicine Software Developers Market in Asia-Pacific and RoW, 2021-2031 (USD Million)
  • Figure 11.11. Precision Medicine Software Developers Market: Distribution by Type of End-User, 2021-2031 (USD Million)
  • Figure 11.12. Precision Medicine Software Developers Market for Healthcare Providers, 2021-2031 (USD Million)
  • Figure 11.13. Precision Medicine Software Developers Market for Research and Government Institutes, 2021-2031 (USD Million)
  • Figure 11.14. Precision Medicine Software Developers Market for Pharmaceutical and Biotech Companies, 2021-2031 (USD Million)
  • Figure 12.1. Precision Medicine Software Developers: SWOT Analysis
  • Figure 12.2. Comparison of SWOT Factors: Harvey Ball Analysis
  • Figure 13.1. Concluding Remarks: Current Market Landscape
  • Figure 13.2. Concluding Remarks: Recent Partnerships
  • Figure 13.3. Concluding Remarks: Funding Analysis
  • Figure 13.4. Concluding Remarks: Cost Saving Analysis
  • Figure 13.5. Concluding Remarks: Market Sizing and Opportunity Analysis