Frost Radar™: Artificial Intelligence-enabled Drug Discovery in the Global Pharmaceutical Industry, 2021

Frost Radar™: Artificial Intelligence-enabled Drug Discovery in the Global Pharmaceutical Industry, 2021

A Benchmarking System to Spark Companies to Action—Innovation that Fuels New Deal Flow and Growth Pipelines

RELEASE DATE
23-Jun-2021
REGION
Global
Deliverable Type
Frost Radar
Research Code: K616-01-00-00-00
SKU: HC03422-GL-MR_25520
AvailableYesPDF Download
$4,950.00
In stock
SKU
HC03422-GL-MR_25520

Frost Radar™: Artificial Intelligence-enabled Drug Discovery in the Global Pharmaceutical Industry, 2021
Published on: 23-Jun-2021 | SKU: HC03422-GL-MR_25520

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Pharmaceutical drug discovery and development suffers from declining success rates with new molecules, and the rate of return has shrunk from 16% in 2011 to almost 11% in 2018. Frost & Sullivan finds that traditional solutions focused primarily on data from limited sources and rule-based computational techniques used to address the understanding of targets and leads are inefficient.

Artificial intelligence (AI) is set to transform the landscape of drug discovery. The application of AI-based products and solutions is enabling the pharmaceutical industry to shorten discovery timelines, enhance process agility, increase prediction accuracy on the efficacy and safety of drugs, and improve the opportunity to diversify drug pipelines using a cost-effective model.

Most vendors are focused on collecting, creating, and augmenting data from across laboratories, clinical trials, real-world evidence, biobanks, and repositories. The increasing volume and veracity of clinical and research data compels traditional providers to leverage enabling tools and technologies such as cloud computing, artificial intelligence (AI), machine learning (ML), natural language processing (NLP), and advanced analytics to make a shift from the slow, traditional approach to a relatively fast, rational data-driven drug discovery and development approach.

To remain competitive it is critical for players to establish the right balance of data, AI, and computational capability and to match it with the wet-lab capability. There remains inadequate understanding of the biological networks and drug-target interactions; here, AI has been able to support the identification and prioritization of disease-specific therapeutic targets based on gene-disease associations. Such results must be replicated and validated through in-vitro experiments and in-vivo models.

Frost & Sullivan finds that the impact of AI on the complete pharma value chain can more than double what is achievable using traditional analytics and capture between 2 and 3% of industry revenue, amounting to more than $50 billion in potential annual impact.

This Frost Radar™ recognizes industry participants that are at the forefront of developing and successfully employing advanced tools. This industry-first benchmarking study provides an introduction to the ecosystem and recognizes pioneering companies. The Radar™ reveals the market positioning of each company using its Growth and Innovation scores as highlighted in the Frost Radar™ methodology. The document presents competitive profiles on each company based on its strengths, opportunities, and market positioning. We discuss strategic market imperatives and the competitive environment that vendors operate in as well as make recommendations for each provider to spur growth.

Author: Amol Dilip Jadhav

Strategic Imperative

Strategic Imperative (continued)

Growth Environment

Frost Radar™: Artificial Intelligence-enabled Drug Discovery in the Global Pharmaceutical Industry

Frost Radar™: Competitive Environment

Frost Radar™: Competitive Environment (continued)

Frost Radar™: Competitive Environment (continued)

Frost Radar™: Competitive Environment (continued)

AbCellera Biologics, Inc.

AI Therapeutics, Inc.

Atomwise

BenevolentAI

BERG Health

Black Diamond Therapeutics

Cellarity

EQRx

Evaxion Biotech

Exscientia Ltd.

Healx

Insilico Medicine

Insitro

Recursion

Relay Therapeutics

Schrödinger

twoXAR

Valo Health

Strategic Insights

Significance of Being on the Frost Radar™

Frost Radar™ Empowers the CEO’s Growth Team

Frost Radar™ Empowers Investors

Frost Radar™ Empowers Customers

Frost Radar™ Empowers the Board of Directors

Frost Radar™: Benchmarking Future Growth Potential

Frost Radar™: Benchmarking Future Growth Potential

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  • Growth Dialog™ with our experts

Growth Dialog™

A tailored session with you where we identify the:
  • Strategic Imperatives
  • Growth Opportunities
  • Best Practices
  • Companies to Action

Impacting your company's future growth potential.

Pharmaceutical drug discovery and development suffers from declining success rates with new molecules, and the rate of return has shrunk from 16% in 2011 to almost 11% in 2018. Frost & Sullivan finds that traditional solutions focused primarily on data from limited sources and rule-based computational techniques used to address the understanding of targets and leads are inefficient. Artificial intelligence (AI) is set to transform the landscape of drug discovery. The application of AI-based products and solutions is enabling the pharmaceutical industry to shorten discovery timelines, enhance process agility, increase prediction accuracy on the efficacy and safety of drugs, and improve the opportunity to diversify drug pipelines using a cost-effective model. Most vendors are focused on collecting, creating, and augmenting data from across laboratories, clinical trials, real-world evidence, biobanks, and repositories. The increasing volume and veracity of clinical and research data compels traditional providers to leverage enabling tools and technologies such as cloud computing, artificial intelligence (AI), machine learning (ML), natural language processing (NLP), and advanced analytics to make a shift from the slow, traditional approach to a relatively fast, rational data-driven drug discovery and development approach. To remain competitive it is critical for players to establish the right balance of data, AI, and computational capability and to match it with the wet-lab capability. There remains inadequate understanding of the biological networks and drug-target interactions; here, AI has been able to support the identification and prioritization of disease-specific therapeutic targets based on gene-disease associations. Such results must be replicated and validated through in-vitro experiments and in-vivo models. Frost & Sullivan finds that the impact of AI on the complete pharma value chain can more than double what is achievable using traditional analytics and capture between 2 and 3% of industry revenue, amounting to more than $50 billion in potential annual impact. This Frost Radar™ recognizes industry participants that are at the forefront of developing and successfully employing advanced tools. This industry-first benchmarking study provides an introduction to the ecosystem and recognizes pioneering companies. The Radar™ reveals the market positioning of each company using its Growth and Innovation scores as highlighted in the Frost Radar™ methodology. The document presents competitive profiles on each company based on its strengths, opportunities, and market positioning. We discuss strategic market imperatives and the competitive environment that vendors operate in as well as make recommendations for each provider to spur growth. Author: Amol Dilip Jadhav
More Information
Deliverable Type Frost Radar
No Index No
Podcast No
Author Amol Dilip Jadhav
Industries Healthcare
WIP Number K616-01-00-00-00
Is Prebook No
GPS Codes 9600-B1,9611-B1