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Deep Learning Market Revenue for in Drug Discovery and Diagnostics to Cross US$ 34.5 Billion by 2035 | Roots Analysis

Published: August 2023


According to a recently published report by Roots Analysis, the potential of deep learning-based technologies to expedite drug discovery process and improve early-stage diagnosis is driving the deep learning in drug discovery market growth

Deep Learning Industry Overview

The global deep learning in drug discovery market is anticipated to grow at a CAGR of 21.9% from 2023-2035, reaching USD 34.5 billion by 2035.

The conventional drug discovery and drug development process is fraught with several challenges, including high attrition rate and increased financial burden. Further, the traditional statistical tools and techniques available for medical data interpretation are known to be time and cost intensive. The distinct characteristics of deep learning algorithm to imitate the human brain has prompted industry stakeholders to explore the applications of deep learning-based technologies, across the life sciences industry, primarily for the purposes of drug discovery and diagnostics. Additionally, recent advancements in the deep learning market have demonstrated its potential in other healthcare-associated segments, such as medical imaging, molecular profiling, virtual screening and data analysis. Further investments made in this domain are likely to offer lucrative opportunities to companies offering deep learning based technologies / solutions within the healthcare industry.

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Market Drivers

In the last decade, the healthcare industry has witnessed an inclination towards the adoption of information services and digital analytical solutions. This can be attributed to the fact that companies have recently shifted towards high-resolution medical images and electronic health and medical records, generating large and complex data, referred to as big data. In order to analyze such large datasets, efficient tools and technology, such as deep learning, are required. Thus, the emergence of big data is anticipated to be a primary driver of the adoption of deep learning and artificial intelligence in the healthcare industry.

Market Restraints

One of the primary restraints associated with this industry include lack of technical competence and lack of regulatory standards and protocols. Owing to the complexity of the deep learning technologies, it requires skilled professionals to manage research and development operations. Further, comparing and analyzing large datasets by bringing them to a centralized repository, prone to data breaches, generates privacy related challenges. These factors, coupled with the additional inherent costs associated with employing trained personnel for work processes poses as an impediment to the application deep learning in healthcare domain.

Growth Factors

Despite the challenges, various factors contribute to the growth of deep learning market in drug discovery and diagnostics. These factors include growing financial burden for drug discovery, early-stage diagnostic capability of deep learning technologies and expedited discovery diagnosis timelines through technological integration. Given that drug discovery and development is considered to be a tedious process, often consuming a significant amount of time and resources and designing a new drug that binds to any specific target requires a large amount of time, as well as computing power, deep learning algorithms have demonstrated vast potential in accelerating this process owing to their ability to mimic the human brain. Considering its time and cost saving ability, drug discovery and diagnostics is gradually shifting from conventional methods to integrating deep learning technologies.

Deep Learning Market Segments

Based on the therapeutic areas, the market is segmented into Oncological Disorders, Infectious Diseases, Neurological Disorders, Immunological Disorders, Endocrine Disorders, Cardiovascular Disorders, Respiratory Disorders and Other Disorders

  • The oncological disorders segment led the market for deep learning in drug discovery, capturing the largest revenue share of close to 38.0% in 2023.
  • The respiratory disorders segment is anticipated to show the highest growth potential during the forecast period of over 2.8% annually.

Based on the key geographical regions, the market is segmented into North America, Europe, Asia Pacific and Rest of the World

  • North America dominated the deep learning in drug discovery market and accounted for the largest revenue share of about 46.0% in 2023.
  • In Europe, the deep learning in drug discovery market is anticipated to demonstrate lucrative growth during the forecast period.

Deep Learning in Diagnostics Market Segments

Based on the therapeutic areas, the market is segmented into Oncological Disorders, Cardiovascular Disorders, Neurological Disorders, Endocrine Disorders, Respiratory Disorders, Ophthalmic Disorders, Infectious Diseases, Musculoskeletal Disorders, Inflammatory Disorders and Other Disorders

  • The oncological disorders segment led the market for deep learning in diagnostics, capturing the largest revenue share of close to 34% in 2023.
  • The musculoskeletal disorders segment is anticipated to show the highest growth potential during the forecast period of over 2.4% annually.

Based on the key geographical regions, the market is segmented into North America, Europe, Asia Pacific and Rest of the World

  • North America dominated the deep learning in drug discovery market and accounted for the largest revenue share of about 37% in 2023.
  • In Asia-Pacific, the deep learning in drug discovery market is anticipated to demonstrate lucrative growth during the forecast period of over 21.1% annually.

Key Companies Profiled

The deep learning in drug discovery market and deep learning in diagnostics market report also includes detailed profiles of key players (listed below) employing deep learning solutions for drug discovery and diagnostics purposes:

  • Aegicare
  • Aiforia Technologies
  • Ardigen
  • Berg
  • Google
  • Huawei
  • Merative
  • Nference
  • NVIDIA
  • Owkin
  • Phenomic AI
  • Pixel AI

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About Roots Analysis

Roots Analysis is a global leader in the pharma / biotech market research. Having worked with over 750 clients worldwide, including Fortune 500 companies, start-ups, academia, venture capitalists and strategic investors for more than a decade, we offer a highly analytical / data-driven perspective to a network of over 450,000 senior industry stakeholders looking for credible market insights. All reports provided by us are structured in a way that enables the reader to develop a thorough perspective on the given subject. Apart from writing reports on identified areas, we provide bespoke research / consulting services dedicated to serve our clients in the best possible way.

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