>中東およびアフリカの創薬市場における人工知能 (AI)、アプリケーション別 (新薬候補、薬物の最適化と転用、前臨床試験と承認、薬物モニタリング、新しい疾患関連ターゲットと経路の発見、疾患メカニズムの理解、情報の集約と統合、仮説の形成と適格性、デノボ薬物設計、古い薬物の薬物ターゲットの発見など)、テクノロジー (機械学習、ディープラーニング、自然言語処理など)、薬物タイプ (小分子と巨大分子)、提供 (ソフトウェアとサービス)、適応症 (免疫腫瘍学、神経変性疾患、心血管疾患、代謝性疾患など)、最終用途 (開発業務受託機関 (CRO)、製薬およびバイオテクノロジー企業、研究センターおよび学術機関など) の業界動向と2029年までの予測。
中東およびアフリカの創薬市場における人工知能 (AI) の分析と洞察
人工知能 (AI) は、ヘルスケア業界では利益を生む技術になると期待されています。AI の導入により、医薬品製造プロセスにおける研究開発ギャップが縮小し、ターゲットを絞った医薬品の製造に役立ちます。そのため、バイオ医薬品企業は市場シェアの拡大に AI を活用しています。医薬品発見のための AI は、機械を使用して人間の知能をシミュレートし、医薬品開発プロセスにおける複雑な課題を解決する技術です。
臨床試験プロセスに AI ソリューションを導入すると、起こり得る障害が排除され、臨床試験のサイクル時間が短縮され、臨床試験プロセスの生産性と精度が向上します。医薬品の発見における AI の技術的進歩と医薬品の発見プロセスにかかる総時間の短縮は、予測期間中の市場の成長を促進する他の要因です。ただし、利用可能なデータの品質が低く一貫性がない場合は、市場の成長が妨げられます。また、テクノロジーに関連するコストの高さと技術的な制限により、市場の成長が抑制されます。
Data Bridge Market Research は、中東およびアフリカの創薬市場における人工知能 (AI) は、予測期間中に 47.1% の CAGR で成長し、2029 年までに 5 億 4,876 万米ドルに達すると予測しています。創薬市場における AI の利用を商業化するための技術進歩が急速に進んでいるため、ソフトウェアは市場で最大の技術セグメントを占めています。この市場レポートでは、価格分析、特許分析、技術進歩についても詳細に取り上げています。
|
レポートメトリック |
詳細 |
|
予測期間 |
2022年から2029年 |
|
基準年 |
2021 |
|
歴史的な年 |
2020 (2019～2014 にカスタマイズ可能) |
|
定量単位 |
売上高は百万米ドル、価格は米ドル |
|
対象セグメント |
By Application (Novel Drug Candidates, Drug Optimization and Repurposing Preclinical Testing and Approval, Drug Monitoring, Finding New Diseases Associated Targets and Pathways, Understanding Disease Mechanisms, Aggregating and Synthesizing Information, Formation & Qualification of Hypotheses, De Novo Drug Design, Finding Drug Targets of an Old Drug and Others), Technology (Machine Learning, Deep Learning, Natural Language Processing and Others), Drug Type (Small Molecule and Large Molecule), Offering (Software and Services), Indication (Immuno-Oncology, Neurodegenerative Diseases, Cardiovascular Diseases, Metabolic Diseases and Others), End Use (Contract Research Organizations (CROs), Pharmaceutical & Biotechnology Companies, Research Centers and Academic Institutes and Others) |
|
Countries Covered |
U.A.E, Israel, South Africa, Saudi Arabia, Egypt, rest of Middle East and Africa |
|
Market Players Covered |
Some of the key players operating in the market are NVIDIA Corporation, IBM Corp., Atomwise Inc., Microsoft, Benevolent AI, Aria Pharmaceuticals, Inc., DEEP GENOMICS, Exscientia, Cloud, Insilico Medicine, Cyclica, NuMedii, Inc., Envisagenics, Owkin Inc., BERG LLC, Schrödinger, Inc., XtalPi Inc., and BIOAGE Inc. among others |
Middle East and Africa Artificial Intelligence (AI) in Drug Discovery Market Definition
AI has caught the attention and minds of medical technology practitioners in the past few years, as several companies and major research laboratories have worked to perfect these technologies for clinical use. The first commercialized demonstrations of how AI (also known as Deep Learning (DL), Machine Learning (ML), or Artificial Neural Networks (ANNs)) could assist clinicians are now available. These systems could lead to a paradigm shift in clinician workflow, and increase productivity while simultaneously enhancing treatment and patient throughput. AI for drug discovery is a technology that uses machines to simulate human intelligence to solve complicated challenges in the drug development procedure. The adoption of AI solutions in the clinical trial process eliminates possible obstacles, reduces clinical trial cycle time, and increases the productivity and accuracy of the clinical trial process. Therefore, the adoption of these advanced AI solutions in drug discovery processes is gaining popularity amongst life science industry stakeholders. In the pharmaceutical sector, it aids in the discovery of novel compounds, therapeutic target identification, and the development of customized medications. AI platforms used for drug discovery can prove to be a feasible option for deriving insights into the discovery of drugs to treat and minimize the severity of various chronic diseases.
Middle East and Africa Artificial Intelligence (AI) in Drug Discovery Market Dynamics
This section deals with understanding the market drivers, advantages, opportunities, restraints, and challenges. All of this is discussed in detail below:
Drivers
- Rise in incidence of chronic diseases propels need for AI in drug discovery
The incidence of chronic diseases is increasing at a rapid pace across the globe. According to the Centers for Disease Control and Prevention (CDC), six in 10 adults in the U.S. have a chronic disease. Furthermore, the CDC also highlights that chronic diseases such as heart disease and diabetes are the leading causes of death in the U.S. Such statistics shed light on the growing prevalence of chronic diseases and the need to bring down the fatality rate caused due to these diseases.
AI platforms used for drug discovery can prove to be a feasible option for deriving insights into the discovery of drugs to treat and minimize the severity of various chronic diseases. Thus, these factors are expected to act as a driver for the market growth during the forecast period.
- Strategic collaborations, partnerships, and products launch
AI has the potential to transform drug discovery by rapidly accelerating the R&D timeline, making drug development cheaper and faster, and improving the probability of approval. AI can also increase the effectiveness of drug repurposing research.
An increase in cross-industry alliances and collaborations drives the market. Rise in relevance of AI in drug discovery & development, and a surge in funding for R&D activities, including AI technology in the field of drug research, are projected to propel the global market growth. Hence, increase in cross-industry collaborations and partnerships is driving the market.
Restraint
- High cost associated with technology and technical limitations
The current healthcare sector is facing several complex challenges, such as the increased cost of drugs and therapies, and society needs specific significant changes in this area. The entire success of AI depends on the availability of a substantial amount of data because these data are used for the subsequent training provided to the system. Access to data from various database providers can incur extra costs for a company. Clinical trials are directed towards establishing the safety and efficacy of a drug product in humans for a particular disease condition and require six to seven years along with a substantial financial investment. However, only one out of ten molecules entering these trials gain successful clearance, which is a massive loss for the industry. These failures can result from inappropriate patient selection, shortage of technical requirements, and poor infrastructure. Thus, increasing costs with the technology is acting as a restraint for the market growth.
Opportunity
-
Rise in the investments for R&D
The rise in R&D activities and increasing adoption of cloud-based services and applications will provide beneficial opportunities for market growth.
The industry of AI in biopharma continues to grow after a long period of sepsis. This is reflected in the ongoing flow of investments and increase in the number of collaborations between pharmaceutical corporations and AI companies in 2021 to the previous years. The Biopharma industry’s growth is largely influenced by the active engagement of leading pharmaceutical corporations in AI-related investments. The number of scientific publications in the field of AI in Biopharma, and research collaborations between pharma companies and AI-expertise vendors are rapidly increasing, yet, some pharma corporations are still critical of AI applications. ML and AI applications in the pharmaceutical and healthcare industries lead to the formation of a new interdisciplinary field of data-driven drug discovery in healthcare. Thus, rise in investment in R&D activities is acting as an opportunity for market growth.
Challenge
- Lack of skilled professionals
The shortage of skilled professionals is expected to hamper the market growth. The employees have to re-train or learn new skill sets to work efficiently on the complex AI machines to get the desired results for the drug. This challenge that prevents full-fledged adoption of AI in the pharmaceutical industry includes the lack of skilled personnel to operate AI-based platforms, limited budget for small organizations, apprehension of replacing humans leading to job loss, skepticism about the data generated by AI, and the black box phenomenon (that is, how the conclusions are reached by the AI platform). The shortage of skills acts as a major hindrance to drug discovery through AI, discouraging companies to adopt AI-based machines for drug discovery.
As skill demands are too high, it has manifested as a challenge to retain and manage skill-specified professionals. Moreover, technological advancement is another aspect that leads to the increased demand for skilled professionals. There is an urgent need for the education of professionals for AI-based technology. Lack of trained and experienced professionals and persistent skill gaps limit the employability prospects and access to quality jobs. It is therefore apparent that the availability of professionals equipped with adequate skills is challenging the market growth.
Post-COVID-19 Impact on Middle East and Africa Artificial Intelligence (AI) In Drug Discovery Market
The COVID-19 outbreak had a beneficial impact on the expansion of AI in drug discovery industry due to its widespread use by various organizations for the identification as well as screening of existing medicines used in the treatment of COVID-19. AI is useful in detecting active chemicals for the prevention of SARS-CoV, HIV, SARS-CoV-2, influenza virus, and others. During the pandemic, economies all over the world relied on AI-based medication discovery rather than traditional vaccine detection processes, which take years to create and are equally expensive, contributing to the growth of the market.
Manufacturers are making various strategic decisions to bounce back post-COVID-19. The players are conducting multiple R&D activities to improve the technology involved in the Wireless microphone. With this, the companies will bring advanced and accurate AI software to the market.
Recent Developments
- In March 2022, NVIDIA Corporation launched Clara Holoscan MGX to develop and deploy real-time AI applications. Clara Holoscan MGX expands the Clara Holoscan platform to provide an all-in-one, medical-grade reference architecture, as well as long-term software support, to accelerate innovation in the medical device industry. This will help the company for better AI performance in health sector for surgery, diagnostics, and drug discovery.
- In May 2022, Benevolent AI, a leading clinical-stage AI-enabled drug discovery company, announced that AstraZeneca has selected an additional novel target for Idiopathic Pulmonary Fibrosis (IPF) for its drug development portfolio, resulting in a milestone payment to Benevolent AI. This is the third novel target from the collaboration that has been identified using the Benevolent Platform across two disease areas, IPF and chronic kidney disease, and subsequently validated and selected for portfolio entry by AstraZeneca. This builds upon the recent extension of the collaboration with AstraZeneca to include two new disease areas, systemic lupus erythematosus, and heart failure, signed in January 2022. This has helped the company to make its collaboration stronger.
Middle East and Africa Artificial Intelligence (AI) In Drug Discovery Market Scope
Middle East and Africa Artificial Intelligence (AI) in drug discovery market is segmented into application, technology, drug type, offering, indication, and end use. The growth among segments helps you analyze niche pockets of growth and strategies to approach the market and determine your core application areas and the difference in your target markets.
APPLICATION
- Novel Drug Candidates
- Drug Optimization and Repurposing Preclinical Testing and Approval
- Drug Monitoring
- Finding New Diseases Associated Targets and Pathways
- Understanding Disease Mechanisms
- Aggregating and Synthesizing Information
- Formation & Qualification of Hypotheses
- De Novo Drug Design
- Finding Drug Targets of an Old Drug
- Others
Based on application, the market is segmented into novel drug candidates, drug optimization and repurposing preclinical testing and approval, drug monitoring, finding new diseases associated targets and pathways, understanding disease mechanisms, aggregating and synthesizing information, formation & qualification of hypotheses, de novo drug design, finding drug targets of an old drug, and others.
TECHNOLOGY
- Machine Learning (ML)
- Deep Learning (DL)
- Natural Language Processing (NLP)
- Others
Based on technology, the market is segmented into Machine Learning (ML), Deep Learning (DL), Natural Language Processing (NLP), and others.
DRUG TYPE
- Small Molecule
- Large Molecule
薬物の種類に基づいて、市場は低分子と高分子に分類されます。
提供
- ソフトウェア
- サービス
提供内容に基づいて、市場はソフトウェアとサービスに分類されます。
表示
- 免疫腫瘍学
- 神経変性疾患
- 心血管疾患
- 代謝性疾患
- その他
適応症に基づいて、市場は免疫腫瘍学、神経変性疾患、心血管疾患、代謝性疾患、その他に分類されます。
最終使用
- 製薬・バイオテクノロジー企業
- 契約研究機関（CRO）
- 研究センターおよび学術機関
- その他
最終用途に基づいて、市場は製薬およびバイオテクノロジー企業、契約研究機関（CRO）、研究センターおよび学術機関、その他に分類されます。
中東およびアフリカの創薬市場における人工知能 (AI) の地域分析/洞察
中東およびアフリカの創薬市場における人工知能 (AI) が分析され、アプリケーション、テクノロジー、薬剤の種類、提供、適応症、および最終用途別に市場規模の情報が提供されます。
この市場レポートで取り上げられている国は、UAE、イスラエル、南アフリカ、サウジアラビア、エジプト、その他の中東およびアフリカ諸国です。
- 2022年には、政府資金の増加により中東とアフリカが優勢になります。南アフリカは、創薬におけるAIの研究開発活動の増加により成長すると予想されます。
レポートの国別セクションでは、市場の現在および将来の傾向に影響を与える国内市場における個別の市場影響要因と規制の変更も提供しています。新規販売、交換販売、国の人口統計、規制行為、輸出入関税などのデータ ポイントは、各国の市場シナリオを予測するために使用される主要な指標の一部です。また、中東およびアフリカのブランドの存在と可用性、地元および国内ブランドとの競争が激しいか少ないために直面する課題、および販売チャネルの影響を考慮しながら、国別データの予測分析を提供します。
競争環境と中東およびアフリカの創薬市場シェア分析における人工知能 (AI)
中東およびアフリカの創薬における人工知能 (AI) 市場の競争状況では、競合他社ごとに詳細が提供されます。詳細には、会社概要、会社の財務状況、収益、市場の可能性、研究開発への投資、新しい市場への取り組み、生産拠点と施設、会社の強みと弱み、製品の発売、製品試験パイプライン、製品の承認、特許、製品の幅と幅、アプリケーションの優位性、技術ライフライン曲線が含まれます。提供されている上記のデータ ポイントは、中東およびアフリカの創薬における人工知能 (AI) 市場への会社の重点にのみ関連しています。
この市場で活動している主要企業としては、NVIDIA Corporation、IBM Corp.、Atomwise Inc.、Microsoft、Benevolent AI、Aria Pharmaceuticals, Inc.、DEEP GENOMICS、Exscientia、Cloud、Insilico Medicine、Cyclica、NuMedii, Inc.、Envisagenics、Owkin Inc.、BERG LLC、Schrödinger, Inc.、XtalPi Inc.、BIOAGE Inc.などが挙げられます。
SKU-
世界初のマーケットインテリジェンスクラウドに関するレポートにオンラインでアクセスする
- インタラクティブなデータ分析ダッシュボード
- 成長の可能性が高い機会のための企業分析ダッシュボード
- カスタマイズとクエリのためのリサーチアナリストアクセス
- インタラクティブなダッシュボードによる競合分析
- 最新ニュース、更新情報、トレンド分析
- 包括的な競合追跡のためのベンチマーク分析のパワーを活用
目次
1 INTRODUCTION
1.1 OBJECTIVES OF THE STUDY
1.2 MARKET DEFINITION
1.3 OVERVIEW OF MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET
1.4 CURRENCY AND PRICING
1.5 LIMITATIONS
1.6 MARKETS COVERED
2 MARKET SEGMENTATION
2.1 MARKETS COVERED
2.2 GEOGRAPHICAL SCOPE
2.3 YEARS CONSIDERED FOR THE STUDY
2.4 DBMR TRIPOD DATA VALIDATION MODEL
2.5 PRIMARY INTERVIEWS WITH KEY OPINION LEADERS
2.6 MULTIVARIATE MODELLING
2.7 MARKET APPLICATION COVERAGE GRID
2.8 SOURCE LIFELINE CURVE
2.9 DBMR MARKET POSITION GRID
2.1 VENDOR SHARE ANALYSIS
2.11 SECONDARY SOURCES
2.12 ASSUMPTIONS
3 EXECUTIVE SUMMARY
4 PREMIUM INSIGHT
4.1 PESTEL ANALYSIS
4.2 PORETSR’S FIVE FORCES
5 MARKET OVERVIEW
5.1 DRIVERS
5.1.1 THE RISE IN INCIDENCE OF CHRONIC DISEASES PROPELS NEED FOR ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY
5.1.2 STRATEGIC COLLABORATIONS, PARTNERSHIPS, AND PRODUCTS LAUNCH
5.1.3 REDUCTION IN TOTAL TIME INVOLVED IN DRUG DISCOVERY PROCESS
5.1.4 ADVANCEMENT OF ARTIFICIAL INTELLIGENCE IN THE HEALTHCARE INDUSTRY
5.2 RESTRAINTS
5.2.1 HIGH COST ASSOCIATED WITH TECHNOLOGY AND TECHNICAL LIMITATIONS
5.2.2 DISADVANTAGES AND RISKS ASSOCIATED WITH AI IN DRUG DISCOVERY
5.2.3 LACK OF AVAILABLE QUALITY DATA
5.3 OPPORTUNITIES
5.3.1 RISE IN THE INVESTMENTS FOR R&D
5.3.2 RISING HEALTHCARE INFRASTRUCTURE
5.3.3 DEVELOPMENT OF NOVEL TOOLS
5.4 CHALLENGES
5.4.1 THE MIDDLE EAST & AFRICA SHORTAGE OF AI TALENT
5.4.2 ETHICAL, LEGAL, AND REGULATORY ISSUES FOR AI ADOPTION IN THE PHARMACEUTICAL SCIENCES
6 MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY OFFERING
6.1 OVERVIEW
6.2 SOFTWARE
6.2.1 INTEGRATED
6.2.2 STANDALONE
6.3 SERVICES
7 MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY TECHNOLOGY
7.1 OVERVIEW
7.2 MACHINE LEARNING (ML)
7.2.1 SUPERVISED LEARNING
7.2.2 UNSUPERVISED LEARNING
7.2.3 REINFORCEMENT LEARNING
7.3 DEEP LEARNING
7.4 NATURAL LANGUAGE PROCESSING (NLP)
7.5 OTHERS
8 MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET , BY DRUG TYPE
8.1 OVERVIEW
8.2 SMALL MOLECULE
8.3 LARGE MOLECULE
9 MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY APPLICATION
9.1 OVERVIEW
9.2 NOVEL DRUG CANDIDATES
9.2.1 PREDICT BIOACTIVITY OF SMALL MOLECULE
9.2.2 IDENTIFY BIOLOGICS TARGET
9.2.3 OTHERS
9.3 DRUG OPTIMISATION AND RE-PURPOSING PRE-CLINICAL TESTING AND APPROVAL
9.4 DRUG MONITORING
9.5 AGGREGATING AND SYNTHESIZING INFORMATION
9.6 DE NOVO DRUG DESIGN
9.7 FINDING DRUG TARGETS OF AN OLD DRUG
9.8 FORMATION & QUALIFICATION OF HYPOTHESES
9.9 UNDERSTANDING DISEASE MECHANISMS
9.1 FINDING NEW DISEASE-ASSOCIATED TARGETS AND PATHWAYS
9.11 OTHERS
10 MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY INDICATION
10.1 OVERVIEW
10.2 IMMUNE-ONCOLOGY
10.2.1 BREAST CANCER
10.2.2 LUNG CANCER
10.2.3 COLORECTAL CANCER
10.2.4 PROSTATE CANCER
10.2.5 PANCREATIC CANCER
10.2.6 BRAIN CANCER
10.2.7 LEUKEMIA
10.2.8 OTHERS
10.3 NEURODEGENERATIVE DISEASES
10.4 CARDIOVASCULAR DISEASES
10.5 METABOLIC DISEASES
10.6 OTHERS
11 MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET , BY END USE
11.1 OVERVIEW
11.2 CONTRACT RESEARCH ORGANIZATIONS
11.3 PHARMACEUTICAL & BIOTECHNOLOGY COMPANIES
11.4 RESEARCH CENTERS AND ACADEMIC INSTITUTES
11.5 OTHERS
12 MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY REGION
12.1 MIDDLE EAST & AFRICA
12.1.1 SOUTH AFRICA
12.1.2 ISRAEL
12.1.3 SAUDI ARABIA
12.1.4 U.A.E
12.1.5 EGYPT
12.1.6 REST OF MIDDLE EAST AND AFRICA
13 MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET: COMPANY LANDSCAPE
13.1 COMPANY SHARE ANALYSIS: MIDDLE EAST & AFRICA
14 SWOT ANALYSIS
15 COMPANY PROFILES
15.1 NVIDIA CORPORATION
15.1.1 COMPANY SNAPSHOT
15.1.2 REVENUE ANALYSIS
15.1.3 COMPANY SHARE ANALYSIS
15.1.4 PRODUCT PORTFOLIO
15.1.5 RECENT DEVELOPMENTS
15.2 MICROSOFT
15.2.1 COMPANY SNAPSHOT
15.2.2 REVENUE ANALYSIS
15.2.3 COMPANY SHARE ANALYSIS
15.2.4 PRODUCT PORTFOLIO
15.2.5 RECENT DEVELOPMENT
15.3 IBM CORP
15.3.1 COMPANY SNAPSHOT
15.3.2 REVENUE ANALYSIS
15.3.3 COMPANY SHARE ANALYSIS
15.3.4 PRODUCT PORTFOLIO
15.3.5 RECENT DEVELOPMENT
15.4 SCHRÖDINGER, INC.
15.4.1 COMPANY SNAPSHOT
15.4.2 REVENUE ANALYSIS
15.4.3 COMPANY SHARE ANALYSIS
15.4.4 PRODUCT PORTFOLIO
15.4.5 RECENT DEVELOPMENTS
15.5 BERG LLC
15.5.1 COMPANY SNAPSHOT
15.5.2 COMPANY SHARE ANALYSIS
15.5.3 PRODUCT PORTFOLIO
15.5.4 RECENT DEVELOPMENTS
15.6 ARDIGEN
15.6.1 COMPANY SNAPSHOT
15.6.2 PRODUCT PORTFOLIO
15.6.3 RECENT DEVELOPMENTS
15.7 EXSCIENTIA
15.7.1 COMPANY SNAPSHOT
15.7.2 REVENUE ANALYSIS
15.7.3 PRODUCT PORTFOLIO
15.7.4 RECENT DEVELOPMENTS
15.8 ARIA PHARMACEUTICALS, INC.
15.8.1 COMPANY SNAPSHOT
15.8.2 PRODUCT PORTFOLIO
15.8.3 RECENT DEVELOPMENTS
15.9 ATOMWISE INC.
15.9.1 COMPANY SNAPSHOT
15.9.2 PRODUCT PORTFOLIO
15.9.3 RECENT DEVELOPMENTS
15.1 BENEVOLENT AI
15.10.1 COMPANY SNAPSHOT
15.10.2 REVENUE ANALYSIS
15.10.3 PRODUCT PORTFOLIO
15.10.4 RECENT DEVELOPMENTS
15.11 BIOAGE INC.,
15.11.1 COMPANY SNAPSHOT
15.11.2 PRODUCT PORTFOLIO
15.11.3 RECENT DEVELOPMENTS
15.12 CLOUD
15.12.1 COMPANY SNAPSHOT
15.12.2 PRODUCT PORTFOLIO
15.12.3 RECENT DEVELOPMENT
15.13 CYCLICA
15.13.1 COMPANY SNAPSHOT
15.13.2 PRODUCT PORTFOLIO
15.13.3 RECENT DEVELOPMENTS
15.14 DEEP GENOMICS
15.14.1 COMPANY SNAPSHOT
15.14.2 PRODUCT PORTFOLIO
15.14.3 RECENT DEVELOPMENTS
15.15 ENVISAGENICS
15.15.1 COMPANY SNAPSHOT
15.15.2 PRODUCT PORTFOLIO
15.15.3 RECENT DEVELOPMENTS
15.16 INSILICO MEDICINE
15.16.1 COMPANY SNAPSHOT
15.16.2 PRODUCT PORTFOLIO
15.16.3 RECENT DEVELOPMENTS
15.17 NUMEDII, INC.
15.17.1 COMPANY SNAPSHOT
15.17.2 PRODUCT PORTFOLIO
15.17.3 RECENT DEVELOPMENT
15.18 OWKIN INC.
15.18.1 COMPANY SNAPSHOT
15.18.2 PRODUCT PORTFOLIO
15.18.3 RECENT DEVELOPMENT
15.19 XTALPI INC.
15.19.1 COMPANY SNAPSHOT
15.19.2 PRODUCT PORTFOLIO
15.19.3 RECENT DEVELOPMENTS
16 QUESTIONNAIRE
17 RELATED REPORTS
表のリスト
TABLE 1 MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY OFFERING, 2020-2029 (USD MILLION)
TABLE 2 MIDDLE EAST & AFRICA SOFTWARE IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY REGION, 2020-2029 (USD MILLION)
TABLE 3 MIDDLE EAST & AFRICA SOFTWARE IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY TYPE, 2020-2029 (USD MILLION)
TABLE 4 MIDDLE EAST & AFRICA SERVICES IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY REGION, 2020-2029 (USD MILLION)
TABLE 5 MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY TECHNOLOGY, 2020-2029 (USD MILLION)
TABLE 6 MIDDLE EAST & AFRICA MACHINE LEARNING (ML) IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY REGION, 2020-2029 (USD MILLION)
TABLE 7 MIDDLE EAST & AFRICA MACHINE LEARNING (ML) IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY TECHNOLOGY, 2020-2029 (USD MILLION)
TABLE 8 MIDDLE EAST & AFRICA DEEP LEARNING IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY REGION, 2020-2029 (USD MILLION)
TABLE 9 MIDDLE EAST & AFRICA NATURAL LANGUAGE PROCESSING (NLP) IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY REGION, 2020-2029 (USD MILLION)
TABLE 10 MIDDLE EAST & AFRICA OTHERS IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY REGION, 2020-2029 (USD MILLION)
TABLE 11 MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY DRUG TYPE, 2020-2029 (USD MILLION)
TABLE 12 MIDDLE EAST & AFRICA SMALL MOLECULE IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY REGION, 2020-2029 (USD MILLION)
TABLE 13 MIDDLE EAST & AFRICA LARGE MOLECULE IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY REGION, 2020-2029 (USD MILLION)
TABLE 14 MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY APPLICATION, 2020-2029 (USD MILLION)
TABLE 15 MIDDLE EAST & AFRICA NOVEL DRUG CANDIDATES IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY REGION, 2020-2029 (USD MILLION)
TABLE 16 MIDDLE EAST & AFRICA NOVEL DRUG CANDIDATES IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY APPLICATION, 2020-2029 (USD MILLION)
TABLE 17 MIDDLE EAST & AFRICA DRUG OPTIMISATION AND RE-PURPOSING PRE-CLINICAL TESTING AND APPROVAL IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY REGION, 2020-2029 (USD MILLION)
TABLE 18 MIDDLE EAST & AFRICA DRUG MONITORING IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY REGION, 2020-2029 (USD MILLION)
TABLE 19 MIDDLE EAST & AFRICA AGGREGATING AND SYNTHESIZING INFORMATION IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY REGION, 2020-2029 (USD MILLION)
TABLE 20 MIDDLE EAST & AFRICA DE NOVO DRUG DESIGN IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY REGION, 2020-2029 (USD MILLION)
TABLE 21 MIDDLE EAST & AFRICA FINDING DRUG TARGETS OF AN OLD DRUG IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY REGION, 2020-2029 (USD MILLION)
TABLE 22 MIDDLE EAST & AFRICA FORMATION & QUALIFICATION OF HYPOTHESES IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY REGION, 2020-2029 (USD MILLION)
TABLE 23 MIDDLE EAST & AFRICA UNDERSTANDING DISEASE MECHANISMS IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY REGION, 2020-2029 (USD MILLION)
TABLE 24 MIDDLE EAST & AFRICA FINDING NEW DISEASE-ASSOCIATED TARGETS AND PATHWAYS IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY REGION, 2020-2029 (USD MILLION)
TABLE 25 MIDDLE EAST & AFRICA OTHERS IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY REGION, 2020-2029 (USD MILLION)
TABLE 26 MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY INDICATION, 2020-2029 (USD MILLION)
TABLE 27 MIDDLE EAST & AFRICA IMMUNO-ONCOLOGY IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY REGION, 2020-2029 (USD MILLION)
TABLE 28 MIDDLE EAST & AFRICA IMMUNO-ONCOLOGY IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY INDICATION, 2020-2029 (USD MILLION)
TABLE 29 MIDDLE EAST & AFRICA NEURODEGENERATIVE DISEASES IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY REGION, 2020-2029 (USD MILLION)
TABLE 30 MIDDLE EAST & AFRICA CARDIOVASCULAR DISEASES IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY REGION, 2020-2029 (USD MILLION)
TABLE 31 MIDDLE EAST & AFRICA METABOLIC DISEASES IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY REGION, 2020-2029 (USD MILLION)
TABLE 32 MIDDLE EAST & AFRICA OTHERS IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY REGION, 2020-2029 (USD MILLION)
TABLE 33 GLOB MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY END USE, 2020-2029 (USD MILLION)
TABLE 34 MIDDLE EAST & AFRICA CONTRACT RESEARCH ORGANIZATIONS IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY REGION, 2020-2029 (USD MILLION)
TABLE 35 MIDDLE EAST & AFRICA PHARMACEUTICAL & BIOTECHNOLOGY COMPANIES IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY REGION, 2020-2029 (USD MILLION)
TABLE 36 MIDDLE EAST & AFRICA RESEARCH CENTRES AND ACADEMIC INSTITUTES IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY REGION, 2020-2029 (USD MILLION)
TABLE 37 MIDDLE EAST & AFRICA OTHERS IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY REGION, 2020-2029 (USD MILLION)
TABLE 38 MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY COUNTRY, 2020-2029 (USD MILLION)
TABLE 39 MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY OFFERING, 2020-2029 (USD MILLION)
TABLE 40 MIDDLE EAST & AFRICA ARTIFICIAL SOFTWARE IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY TYPE, 2020-2029 (USD MILLION)
TABLE 41 MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY TECHNOLOGY, 2020-2029 (USD MILLION)
TABLE 42 MIDDLE EAST & AFRICA ARTIFICIAL MACHINE LEARNING (ML) IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY TECHNOLOGY, 2020-2029 (USD MILLION)
TABLE 43 MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY DRUG TYPE, 2020-2029 (USD MILLION)
TABLE 44 MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY APPLICATION, 2020-2029 (USD MILLION)
TABLE 45 MIDDLE EAST & AFRICA ARTIFICIAL NOVEL DRUG CANDIDATES IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY APPLICATION, 2020-2029 (USD MILLION)
TABLE 46 MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY INDICATION, 2020-2029 (USD MILLION)
TABLE 47 MIDDLE EAST & AFRICA ARTIFICIAL IMMUNO-ONCOLOGY IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY INDICATION, 2020-2029 (USD MILLION)
TABLE 48 MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY END USE, 2020-2029 (USD MILLION)
TABLE 49 SOUTH AFRICA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY OFFERING, 2020-2029 (USD MILLION)
TABLE 50 SOUTH AFRICA SOFTWARE IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY TYPE, 2020-2029 (USD MILLION)
TABLE 51 SOUTH AFRICA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY TECHNOLOGY, 2020-2029 (USD MILLION)
TABLE 52 SOUTH AFRICA MACHINE LEARNING (ML) IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY TECHNOLOGY, 2020-2029 (USD MILLION)
TABLE 53 SOUTH AFRICA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY DRUG TYPE, 2020-2029 (USD MILLION)
TABLE 54 SOUTH AFRICA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY APPLICATION, 2020-2029 (USD MILLION)
TABLE 55 SOUTH AFRICA NOVEL DRUG CANDIDATES IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY APPLICATION, 2020-2029 (USD MILLION)
TABLE 56 SOUTH AFRICA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY INDICATION, 2020-2029 (USD MILLION)
TABLE 57 SOUTH AFRICA IMMUNO-ONCOLOGY IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY INDICATION, 2020-2029 (USD MILLION)
TABLE 58 SOUTH AFRICA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY END USE, 2020-2029 (USD MILLION)
TABLE 59 ISRAEL ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY OFFERING, 2020-2029 (USD MILLION)
TABLE 60 ISRAEL SOFTWARE IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY TYPE, 2020-2029 (USD MILLION)
TABLE 61 ISRAEL ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY TECHNOLOGY, 2020-2029 (USD MILLION)
TABLE 62 ISRAEL MACHINE LEARNING (ML) IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY TECHNOLOGY, 2020-2029 (USD MILLION)
TABLE 63 ISRAEL ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY DRUG TYPE, 2020-2029 (USD MILLION)
TABLE 64 ISRAEL ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY APPLICATION, 2020-2029 (USD MILLION)
TABLE 65 ISRAEL NOVEL DRUG CANDIDATES IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY APPLICATION, 2020-2029 (USD MILLION)
TABLE 66 ISRAEL ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY INDICATION, 2020-2029 (USD MILLION)
TABLE 67 ISRAEL IMMUNO-ONCOLOGY IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY INDICATION, 2020-2029 (USD MILLION)
TABLE 68 ISRAEL ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY END USE, 2020-2029 (USD MILLION)
TABLE 69 SAUDI ARABIA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY OFFERING, 2020-2029 (USD MILLION)
TABLE 70 SAUDI ARABIA SOFTWARE IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY TYPE, 2020-2029 (USD MILLION)
TABLE 71 SAUDI ARABIA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY TECHNOLOGY, 2020-2029 (USD MILLION)
TABLE 72 SAUDI ARABIA MACHINE LEARNING (ML) IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY TECHNOLOGY, 2020-2029 (USD MILLION)
TABLE 73 SAUDI ARABIA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY DRUG TYPE, 2020-2029 (USD MILLION)
TABLE 74 SAUDI ARABIA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY APPLICATION, 2020-2029 (USD MILLION)
TABLE 75 SAUDI ARABIA NOVEL DRUG CANDIDATES IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY APPLICATION, 2020-2029 (USD MILLION)
TABLE 76 SAUDI ARABIA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY INDICATION, 2020-2029 (USD MILLION)
TABLE 77 SAUDI ARABIA IMMUNO-ONCOLOGY IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY INDICATION, 2020-2029 (USD MILLION)
TABLE 78 SAUDI ARABIA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY END USE, 2020-2029 (USD MILLION)
TABLE 79 U.A.E ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY OFFERING, 2020-2029 (USD MILLION)
TABLE 80 U.A.E SOFTWARE IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY TYPE, 2020-2029 (USD MILLION)
TABLE 81 U.A.E ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY TECHNOLOGY, 2020-2029 (USD MILLION)
TABLE 82 U.A.E MACHINE LEARNING (ML) IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY TECHNOLOGY, 2020-2029 (USD MILLION)
TABLE 83 U.A.E ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY DRUG TYPE, 2020-2029 (USD MILLION)
TABLE 84 U.A.E ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY APPLICATION, 2020-2029 (USD MILLION)
TABLE 85 U.A.E NOVEL DRUG CANDIDATES IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY APPLICATION, 2020-2029 (USD MILLION)
TABLE 86 U.A.E ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY INDICATION, 2020-2029 (USD MILLION)
TABLE 87 U.A.E IMMUNO-ONCOLOGY IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY INDICATION, 2020-2029 (USD MILLION)
TABLE 88 U.A.E ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY END USE, 2020-2029 (USD MILLION)
TABLE 89 EGYPT ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY OFFERING, 2020-2029 (USD MILLION)
TABLE 90 EGYPT SOFTWARE IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY TYPE, 2020-2029 (USD MILLION)
TABLE 91 EGYPT ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY TECHNOLOGY, 2020-2029 (USD MILLION)
TABLE 92 EGYPT MACHINE LEARNING (ML) IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY TECHNOLOGY, 2020-2029 (USD MILLION)
TABLE 93 EGYPT ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY DRUG TYPE, 2020-2029 (USD MILLION)
TABLE 94 EGYPT ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY APPLICATION, 2020-2029 (USD MILLION)
TABLE 95 EGYPT NOVEL DRUG CANDIDATES IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY APPLICATION, 2020-2029 (USD MILLION)
TABLE 96 EGYPT ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY INDICATION, 2020-2029 (USD MILLION)
TABLE 97 EGYPT IMMUNO-ONCOLOGY IN ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY INDICATION, 2020-2029 (USD MILLION)
TABLE 98 EGYPT ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY END USE, 2020-2029 (USD MILLION)
TABLE 99 REST OF MIDDLE EAST AND AFRICA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET, BY OFFERING, 2020-2029 (USD MILLION)
図表一覧
FIGURE 1 MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET: SEGMENTATION
FIGURE 2 MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET: DATA TRIANGULATION
FIGURE 3 MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET: DROC ANALYSIS
FIGURE 4 MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET: MIDDLE EAST & AFRICA VS REGIONAL MARKET ANALYSIS
FIGURE 5 MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET: COMPANY RESEARCH ANALYSIS
FIGURE 6 MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET: INTERVIEW DEMOGRAPHICS
FIGURE 7 MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET: MARKET APPLICATION COVERAGE GRID
FIGURE 8 MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET: DBMR MARKET POSITION GRID
FIGURE 9 MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET: VENDOR SHARE ANALYSIS
FIGURE 10 MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET: SEGMENTATION
FIGURE 11 THE GROWING NEED TO CURB DRUG DISCOVERY COSTS AND REDUCE TIME INVOLVED IN THE DRUG DEVELOPMENT PROCESS, THE RISING ADOPTION OF CLOUD-BASED APPLICATIONS AND SERVICES, AND THE IMPENDING PATENT EXPIRY OF BLOCKBUSTER DRUGS ARE EXPECTED TO DRIVE THE GROWTH OF THE MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET IN THE FORECAST PERIOD OF 2022 TO 2029
FIGURE 12 SOFTWARE IS EXPECTED TO ACCOUNT FOR THE LARGEST SHARE OF THE MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET IN 2022 AND 2029
FIGURE 13 DRIVERS, RESTRAINTS, OPPORTUNITIES, AND CHALLENGES OF THE MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET
FIGURE 14 MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET: BY OFFERING, 2021
FIGURE 15 MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET: BY OFFERING, 2022-2029 (USD MILLION)
FIGURE 16 MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET: BY OFFERING, CAGR (2022-2029)
FIGURE 17 MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET: BY OFFERING, LIFELINE CURVE
FIGURE 18 MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET: BY TECHNOLOGY, 2021
FIGURE 19 MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET: BY TECHNOLOGY, 2022-2029 (USD MILLION)
FIGURE 20 MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET: BY TECHNOLOGY, CAGR (2022-2029)
FIGURE 21 MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET: BY TECHNOLOGY, LIFELINE CURVE
FIGURE 22 MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET : BY DRUG TYPE, 2021
FIGURE 23 MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET : BY DRUG TYPE, 2022-2029 (USD MILLION)
FIGURE 24 MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET : BY DRUG TYPE, CAGR (2022-2029)
FIGURE 25 MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET : BY DRUG TYPE, LIFELINE CURVE
FIGURE 26 MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET: BY APPLICATION, 2021
FIGURE 27 MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET: BY APPLICATION, 2020-2029 (USD MILLION)
FIGURE 28 MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET: BY APPLICATION, CAGR (2022-2029)
FIGURE 29 MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET: BY APPLICATION, LIFELINE CURVE
FIGURE 30 MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET: BY INDICATION, 2021
FIGURE 31 MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET: BY INDICATION, 2020-2029 (USD MILLION)
FIGURE 32 MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET: BY INDICATION, CAGR (2022-2029)
FIGURE 33 MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET: BY INDICATION, LIFELINE CURVE
FIGURE 34 MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET: BY END USE, 2021
FIGURE 35 MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET: BY END USE, 2022-2029 (USD MILLION)
FIGURE 36 MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET : BY END USE, CAGR (2022-2029)
FIGURE 37 MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET : BY END USE, LIFELINE CURVE
FIGURE 38 MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET: SNAPSHOT (2021)
FIGURE 39 MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET: BY COUNTRY (2021)
FIGURE 40 MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET: BY COUNTRY (2022 & 2029)
FIGURE 41 MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET: BY COUNTRY (2021 & 2029)
FIGURE 42 MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET: BY OFFERING (2022-2029)
FIGURE 43 MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE (AI) IN DRUG DISCOVERY MARKET: COMPANY SHARE 2021 (%)
調査方法
データ収集と基準年分析は、大規模なサンプル サイズのデータ収集モジュールを使用して行われます。この段階では、さまざまなソースと戦略を通じて市場情報または関連データを取得します。過去に取得したすべてのデータを事前に調査および計画することも含まれます。また、さまざまな情報ソース間で見られる情報の不一致の調査も含まれます。市場データは、市場統計モデルと一貫性モデルを使用して分析および推定されます。また、市場シェア分析と主要トレンド分析は、市場レポートの主要な成功要因です。詳細については、アナリストへの電話をリクエストするか、お問い合わせをドロップダウンしてください。
DBMR 調査チームが使用する主要な調査方法は、データ マイニング、データ変数が市場に与える影響の分析、および一次 (業界の専門家) 検証を含むデータ三角測量です。データ モデルには、ベンダー ポジショニング グリッド、市場タイムライン分析、市場概要とガイド、企業ポジショニング グリッド、特許分析、価格分析、企業市場シェア分析、測定基準、グローバルと地域、ベンダー シェア分析が含まれます。調査方法について詳しくは、お問い合わせフォームから当社の業界専門家にご相談ください。
カスタマイズ可能
Data Bridge Market Research は、高度な形成的調査のリーダーです。当社は、既存および新規のお客様に、お客様の目標に合致し、それに適したデータと分析を提供することに誇りを持っています。レポートは、対象ブランドの価格動向分析、追加国の市場理解 (国のリストをお問い合わせください)、臨床試験結果データ、文献レビュー、リファービッシュ市場および製品ベース分析を含めるようにカスタマイズできます。対象競合他社の市場分析は、技術ベースの分析から市場ポートフォリオ戦略まで分析できます。必要な競合他社のデータを、必要な形式とデータ スタイルでいくつでも追加できます。当社のアナリスト チームは、粗い生の Excel ファイル ピボット テーブル (ファクト ブック) でデータを提供したり、レポートで利用可能なデータ セットからプレゼンテーションを作成するお手伝いをしたりすることもできます。
