In-Silico Drug Discovery Market Size & Share Analysis - Trends, Drivers, Competitive Landscape, and Forecasts (2024 - 2030)

In-Silico Drug Discovery Market Data

In-Silico Drug Discovery Market Analysis

The global in-silico drug discovery market was valued at $2,829.7 million in 2023, and the market size is predicted to reach $5,691.4 million by 2030, advancing at a CAGR of 10.6% during 2024–2030. The market is driven by the increasing focus on reducing medication errors, technological advancements in computational biology, and growing use of cloud-based applications in drug discovery.

In the domain of biomedicine, from preclinical discoveries to late-stage clinical development, in-silico drug design can be useful at all stages of drug development. Such methods aid in the selection of only the most-potent lead molecule, thereby potentially preventing late-stage clinical failures and resulting in cost savings. In-silico design is being employed to hasten and ease hit identification and hit-to-lead selection, improve absorption, distribution, metabolism, excretion, and toxicity profiles, and prevent safety concerns.

Due to the uncontrollable spread of the coronavirus, extensive research was conducted on different types of molecules to understand the morphology of the virus, in order to find a cure. Numerous efforts were undertaken to develop computational drugs by focusing on the primary protease of SARS-CoV2. Docking was done after high-throughput virtual screening of databases including millions of molecules and natural compounds. Thus, due to the incessant efforts for the discovery of specific drugs for COVID–19, there was a positive impact on the in-silico drug discovery market.

In-Silico Drug Discovery Market Trends & Drivers

Technological Advancement in Computational Biology

• The global in-silico drug discovery industry is also driven by the rapid technical breakthroughs in the field of computational biology. Computational approaches have been successful in the development of new medicinal molecules.
• Computational biology advances have further simplified the data processing and analysis phases of sequencing, thus resulting in shorter turnaround times and higher accuracy.
• These improvements have prompted a demand for more-integrated storage and computational node utilization approaches across the industry. Such integration is projected to reduce data transfer costs and eliminate the bottlenecks in downstream analysis and computational analytic community communication.
• Virtual screening is a frequently used computational method for identifying hits in the early phases of the drug development process.

Growing Use of Cloud-Based Applications in Drug Discovery Methods is Driving the Market

• The increasing adoption of cloud-based applications is driving the in-silico drug discovery market. Researchers studying pharmaceuticals can scale up or down their computing environment according to their needs because cloud computing offers access to nearly limitless computational resources.
• Businesses can more readily adapt solutions to meet their unique needs. In order to ensure that the required applications function across pipelines, for example, BT's Cloud Compute life sciences platform can provide specific pharmaceutical applications across the value chain, from discovery to commercial operations, as opposed to imposing one application on every pipeline team.
• By enabling drug developers to analyze historical data, to perform their respective clinical research activities, these applications improve overall productivity and minimize the chances of clinical failure.

Market Segment Breakdown

Technology Analysis

Artificial intelligence held the larger market share, of more than 65%, in 2023. As the data digitization rate is increasing in the healthcare sector, AI is being used to address difficulties such as acquiring, analyzing, and using knowledge to solve complicated clinical problems. AI simulates human intelligence and can distinguish hit-and-lead compounds, thus allowing for faster therapeutic target validation and structural design optimization. Thus, it is being used effectively in different stages of drug discovery, including drug design, chemical synthesis, drug screening, polypharmacology, and drug repurposing.

Technology covered in the report include:

• Artificial Intelligence (Larger and Faster-Growing Category)
• Others

Product Insights

In the in-silico drug discovery market, SaaS is predicted to grow with the highest CAGR, of around 10.8%, in the forecast period. This will primarily be because these solutions help users in data mining, data analysis, and decision making, by offering decentralization, real-world management of data, and many more functionalities. In addition, these solutions help reduce the overall cost and duration of the drug discovery process. Furthermore, they are being widely adopted for virtual screening and target fishing in the drug discovery procedure.

The following products are included in the report:

• Software
• Software-as-a-Service (Largest and Fastest-Growing Category)
• Consultancy-as-a-Service 

End User Overview

• Contract research organizations will witness the fastest growth, with a CAGR of more than 11.0%, during 2024–2030. CROs are reducing the costs for companies developing new medicines.
• Moreover, working with a CRO provides a sponsor with immediate access to almost everything they require to run a successful clinical research program.
• Moreover, pharmacophore modeling software held the largest share in 2021, as its usage in the rational design of new medications has become common. The idea of pharmacophore can be applied to ADME-tox modeling and off-target prediction. Furthermore, to improve virtual screening, the method is frequently used with molecular docking simulations.
• At the root, computer-assisted drug development is a result of artificial intelligence. The extensive use of machine learning, particularly deep learning, in a variety of scientific areas, as well as the developments in computing hardware and software, are all contributing to this revolution. De novo design uses AI to guide the creation of new biologically active molecules with desired properties, whereas the graphics processing unit offers the power of a small computer cluster. AI is being widely used in virtual screening and molecular dynamics simulations.

End user covered in the report are:

• Pharmaceutical and Biopharmaceutical Companies
• Contract Research Organizations (Largest and Fastest-Growing Category)
• Academic and Research Institutes
• Others

Workflow Insights 

Pre-clinical tests held the largest share in 2023. This is attributed to the increasing complexity of diseases, the need for more effective therapies, and regulatory requirements have all contributed to the rising number of preclinical trials being conducted.

It is further classified as:

• Discovery
• Pre-Clinical Tests (Largest and Fastest-Growing Category)
• Clinical Tests 

North America Holds 50% Share Globally

• The North American in-silico drug discovery market held the largest share, of around 50%, in 2023. This is attributed to the strong need for treatments for rare diseases, such as cystic fibrosis and Lou Gehrig's disease.
• Moreover, the R&D expenditure of biopharmaceutical companies is rising in the U.S. In 2020, U.S. medical and R&D investment reached around $250 billion. The market's expansion can also be linked to a better-developed network between service providers and manufacturers than in any other region.
• Additionally, the contribution of the U.S. FDA has helped in the development of a flexible regulatory pathway and resolved several queries about the co-development process.
• Moreover, presence of strong vendors, advancement in technology, a growing population of patient who are suffering from a variety of infectious and chronic diseases, and rising government focus on improving healthcare infrastructure are driving the market.
• The APAC in-silico drug discovery market has seen remarkable growth in software-based technologies, and various programs have been launched to support research on in-silico drug discovery solutions, for improved patient health. Moreover, Japan has been actively implementing health information systems for integrating various functionalities in its hospitals.
• In the same vein, Indian hospitals are quickly implementing clinical information systems to automate their departments and transition from paper-based to digital records for both departments and patients. Major super-specialty hospitals have already begun to use electronic clinical documentation technologies.

Further, regions and countries analyzed for this report include:

• North America (Largest Regional Market)
  • U.S. (Larger and Faster-Growing Country Market)
  • Canada
• Europe
  • Germany (Largest Country Market)
  • U.K. (Fastest-Growing Country Market)
  • France
  • Italy
  • Spain
  • Rest of Europe
• Asia-Pacific (APAC) (Fastest-Growing Regional Market)
  • China (Largest Country Market)
  • Japan
  • India (Fastest-Growing Country Market)
  • South Korea
  • Australia
  • Rest of APAC
• Latin America (LATAM)
  • Brazil (Largest and Fastest-Growing Country Market)
  • Mexico
  • Rest of LATAM
• Middle East and Africa (MEA)
  • Saudi Arabia (Largest Country Market)
  • South Africa
  • U.A.E. (Fastest-Growing Country Market)
  • Rest of MEA

Market Nature - Fragmented

The market is fragmented in nature with the presence of several major players. In recent years, they have pursued partnerships & collaborations in order to stay ahead of their competitors.

In-Silico Drug Discovery Industry News

• Insilico Medicine announced the nomination of a preclinical candidate for idiopathic pulmonary fibrosis (IPF) in February 2024 for a new antifibrotic target, both discovered using the company’s Pharma.AI platform.
• Insilico Medicine and University of Zurich collaborated in March 2022 for utilizing the generative AI technology of Insilico Mdicine for finding out a novel treatment for cystinosis.
• Insilico Medicine and Fosun Pharma partnered in January 2022. Under this, Fosun Pharma's clinical development and commercial experience was combined with Insilico's AI-driven drug discovery platforms to create a new therapeutic portfolio.