Healthcare

Data Science Impacting the Pharmaceutical Industry Part II: Clinical trial Applications

Enabling faster analysis using advanced tools

INDUSTRY
Healthcare

RELEASE DATE
31-Aug-2020
REGION
DELIVERABLE TYPE
Technology Research

RESEARCH CODE
D9B1-01-00-00-00
SKU
HC03334-GL-TR_24701
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Data Science Impacting the Pharmaceutical Industry Part II: Clinical trial Applications
Published on: 31-Aug-2020 | SKU: HC03334-GL-TR_24701

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Clinical Trials, the most crucial step in drug discovery has never been in the forefront in adopting new technologies and transforming from the conventional protocols. With the development of AI/ML in the last five years, it has opened up a new horizon for transforming clinical trials. It has been proven that use of AI/ML tools can scan through large volumes of data and provide accurate results within minutes which takes enormous time when performed by humans. Application of analytical tools help identify trends and patterns that may have been difficult to observe otherwise and provide results in the best possible way.

The Strategic Imperative 8™

The Strategic Imperative 8™

The Impact of the Top Three Strategic Imperatives on the Data Science Industry

About The Growth Pipeline Engine™

Growth Opportunities Fuel the Growth Pipeline Engine™

Research Methodology

Key Findings

1.1 Clinical Trials Still the most Complex Step in the Lifecycle of Drug Development

1.2 Following Conventional Steps in Clinical Trials is an Ongoing Challenge

1.3 Importance of Data Science in Clinical Trials

1.4 Important Terminologies Associated with Data Science and its Role

2.1 Adoption of Data Science in Clinical Trials is Seen across the Globe

2.2 Key Factors to Leverage Use of Data Science in Clinical Trials

2.3 NLP and OCR are Extensively Used in Data Structuring

2.4 Data Science Taps Untapped Significant Information

2.5 Data science Tools Help Reduce Clinical Trial Timeline

2.6 Downstream Workflow of Data Science Tools

2.7 Medical Data Conversion to E health Data is an Essential Step

3.1 AI Based Models Provide Predictive Solutions

3.2 Data Driven Models’ Focus Areas

3.3 Key Challenges in Patient Enrollment

3.4 Use of Digital Platforms Increases Patient Retention

3.5 Role of Data Science in Leveraging Cancer Treatments

3.6 Role of Data Science in the Rare Disease Area

3.7 Enabling Virtual Clinical Trials Using Data Science during COVID-19

3.8 AI Tools Speed up Patient Recruitment

3.9 Data Sharing to be Driving Factor in AI Enabled Clinical Trials

4.1 Collaboration between Big Pharma and AI Companies to Leverage Clinical Trials

4.2 Tech Companies Come together to Pool Resources

4.3 Mendel.ai

4.4 Ai Cure

4.5 Inato

4.6 GNS Healthcare

4.7 Trials.ai

4.8 Antidote

4.9 Deep 6 Ai

4.10 BullFrog Ai

4.11 PathAI

4.12 Tempus

5.1 IP Overview of Data Science in Pharmaceutical Development

5.2 Top Patent List

5.3 Top Patents in Screening Patients Technology

5.4 Top Patents in Structured Platforms

6.1 Growth opportunity 1: Data Science driven Patient Selection

6.1 Growth Opportunity 1: Data Science-driven Patient Selection

6.2 Growth opportunity 2: FDA accelerated Data sharing has opened many opportunities

6.2 Growth Opportunity 2: FDA accelerated sharing has opened many opportunities (continued)

Abbreviation

Key Industry Contacts

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