AI-Friendly CEOs and Board Members in Pharma and Tech Corporations

By Margaretta Colangelo, Managing Partner at Deep Knowledge Ventures. View original article here.

Today Deep Knowledge Analytics published AI-Friendly CEOs and Board Members in Pharma and Tech Corporations. This special report is based on comprehensive research on 50 pharma and tech corporations that are applying AI in advanced biomedicine. This open access report identifies 100 CEOs and board members who are driving the implementation of AI in biomedicine and supporting the growth of AI globally. The presence of AI-friendly CEOs and board members is an indication that a company is focused on increasing R&D efficiency and thus is more likely to succeed in the drug discovery and advanced healthcare sectors. The objective of this report is to establish a benchmark. In the future we expect to observe a correlation between such benchmarking and market and investment prospects with the level of AI commitment serving as an indicator of market capitalization growth.

 

Report Highlights

  • The distribution of AI-friendly CEOs and board members is concentrated in the US, Germany, and Japan. These countries are likely to become AI research and innovation hubs that attract AI in Pharma experts from around the world.
  • The cities with the highest numbers of AI-friendly CEOs and board members are New York, San Francisco, Indianapolis, Ingelheim am Rhein, Basel, and Tokyo.

  • The AI leaders have strong interdisciplinary skills in both business and technology.
  • The AI leaders possess deep experience in areas such as computer science, AI, data science, engineering, statistics, math, and life sciences, and have a high number of peer-reviewed publications and a high level of citation.

  • 54% of the AI leaders work in tech companies.
  • 46% of the AI leaders work in pharma companies.
  • 3% of the AI leaders have experience and education in both AI and drug development.

Pharma AI Stock Index

We expect the presence of AI-friendly CEOs and board members to enable companies to outperform general market trends in the sector via a more effective and complex application of AI. Similarly, the growth of the Pharma AI Stock Index will exceed the growth of most traditional market indices. Our Pharma AI Stock Index proprietary report aims to assess financial dynamics of pharma and tech companies applying AI for drug discovery and advanced healthcare in order to enable investors, companies and other industry participants to develop effective short and long-term strategies. The application of AI adds a new dimension that is used by the financial community to determine current and future market valuations of organizations. The use of AI by companies will become a standard component analyzed by fund managers to evaluate companies for investment.

The report includes the following charts and lists

  • 25 Pharma Corporations Applying AI for Drug Discovery
  • 25 Tech Corporations Applying Advanced AI Technologies in Healthcare
  • 100 AI-Friendly CEOs and Board Members
  • AI-Friendly CEOs and Board Members by Type of Corporation

  • 100 AI-Friendly CEOs and Board Members by Location
  • Specialization of 100 AI-Friendly CEOs and Board Members
  • 100 AI-Friendly CEOs and Board Members Distribution by Position
  • Pharma Corporation Collaborations with AI Companies

  • Research Associations between Pharmaceutical and Tech Corporations
  • Scientific Publications about AI in Drug Discovery
  • Financial Indicators

Methodology

An initial pool of 300 candidates with interdisciplinary skills in both business and technology was selected from multiple sources including articles, awards, research citations, books, talks, social media activity, and education. Categorical variables were considered to be dimensions, descriptive attributes for univariate and bivariate analysis, and classification. Numerical variables were considered to be measures of the initial dataset.

The initial pool was shortlisted down to 100 following an iterative approach, starting with differentiating parameters and gradually specifying additional parameters for the final rating. The ranking calculation model is a first-order homogeneous polynomial that calculates a person’s assessment variables and their relative impact weights (coefficients). Numeric variables were standardized. The weights of each variable have been logically designed to underline major contributions and impact (innovations, business achievement) and only augment them with less important, yet valuable, contributions (conference talks, social media activity). The most emphasis was placed on the activities of CEOs and board members in their corporations regarding AI applications and development.

Future Editions

In the next edition, the list of CEOs and board members will be expanded to 150 executives from a broadened number of companies in the pharmaceutical and technology industries. The main focus will be on the contribution of market makers in development of AI technologies for drug discovery and implementation of powered deep learning techniques into research and development of new medical treatments. Information will be displayed with interactive mind maps, graphs and spreadsheets.

  • CEOs and board members will be ranked by the impact of their work in deep learning.
  • We will identify which companies are key players in implementation of AI.
  • We will provide the ranking of AI-friendly executives across industries.
  • We will describe how DL techniques for drug discovery can be measured and evaluated.
  • We will provide a thorough analysis of the performance of pharma and tech companies in relation to AI for Drug Discovery.
  • We will provide an analysis of key market players in the AI for Drug Discovery and Biomarker Development landscape.
  • To see profiles for all 100 AI-friendly CEOs and board members and read the full report please click on the link below to download the report.

AI-Friendly CEOs and Board Members of Pharma and Tech Corporations

About Deep Knowledge Analytics

Deep Knowledge Analytics is the DeepTech analytical arm of Deep Knowledge Ventures, specializing in forecasting the convergence of technological mega-trends, conducting special case studies, and producing advanced industry analytical reports on the topics of AI, DeepTech, GovTech, FinTech and InvestTech. DKA’s Pharma Division is the leading analytical entity specifically focused on providing deep intelligence on the Pharma industry and the AI for Drug Discovery sector, and serves as the main source of market intelligence and analytics for AI-Pharma, a specialized hybrid hedge fund. @DK_Analytics

This article was written by Margaretta Colangelo and Dmitry Kaminskiy.

Margaretta Colangelo, Managing Partner at Deep Knowledge Ventures, is based in San Francisco. Margaretta serves on the Advisory Board of the AI Precision Health Institute at the University of Hawai‘i Cancer Center.

Dmitry Kaminskiy, General Partner at Deep Knowledge Ventures, is based in London. Dmitry is Head of International Development of the Secretariat for the All Party Parliamentary Group for Longevity and Managing Trustee of the Biogerontology Research Foundation. @DeepTech_VC

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