Research Methodology – Artificial Intelligence for Drug Discovery and Development Market
At Straits Research, we adopt a rigorous 360° research approach that integrates both primary and secondary research methodologies. This ensures accuracy, reliability, and actionable insights for stakeholders. Our methodology for the Artificial Intelligence for Drug Discovery and Development Market comprises the following key stages:
Market Indicator & Macro-Factor Analysis
Our baseline thesis for the Artificial Intelligence for Drug Discovery and Development Market is developed by integrating key market indicators and macroeconomic variables. These include:
Factors considered while calculating market size and share
- The number of pharmaceutical and biotechnological companies adopting AI for drug discovery and development.
- Investments in AI technologies by the pharmaceutical and healthcare industries.
- The impact of governmental regulations and policies on AI in healthcare.
- The level of competition in the market.
- Market penetration and growth of AI in different geographic regions, especially in developed and developing countries.
- Economical capabilities of the companies involved in AI for drug discovery and development.
Key Market Indicators
- The annual growth rate of the AI for drug discovery and development market.
- Revenue generated by AI in drug discovery and development.
- Number of patented AI algorithms and technologies specific to drug discovery and development.
- Pharmaceutical spending on AI research and development.
- Number of start-ups and new entrants in the market.
- Partnerships and collaborations between AI companies and pharmaceutical companies.
Growth Trends
- Increased use of AI in predicting drug efficiency and reducing drug discovery costs.
- Growth in partnerships between AI technology providers and pharmaceutical companies.
- Technological advancements in AI algorithms for drug discovery.
- Increasing demand for personalized medicine driving the use of AI.
- Increased adoption of cloud-based applications and services in drug discovery and development.
- Rise in demand for reducing drug discovery timelines through the use of AI.
Secondary Research
Our secondary research forms the foundation of market understanding and scope definition. We collect and analyze information from multiple reliable sources to map the overall ecosystem of the Artificial Intelligence for Drug Discovery and Development Market. Key inputs include:
- Annual reports, investor presentations, SEC filings
- Company press releases and product launch announcements
- Public executive interviews and earnings calls
- Strategy briefings and M&A updates
- Country-level industry associations and trade bodies
- Government dossiers, policy frameworks, and official releases
- Whitepapers, working papers, and public R&D initiatives
- Relevant Associations for the Artificial Intelligence for Drug Discovery and Development Market
- Broker reports and financial analyst coverage
- Paid databases (Hoovers, Factiva, Refinitiv, Reuters, Statista, etc.)
- Import/export trade data and tariff databases
- Sector-specific journals, magazines, and news portals
- Global macroeconomic indicators and their cascading effect on the industry
- Demand–supply outlook and value chain analysis
- Consumer behaviour, adoption rates, and commercialization trends
Primary Research
To validate and enrich our secondary findings, we conduct extensive primary research with industry stakeholders across the value chain. This ensures we capture both qualitative insights and quantitative validation. Our primary research includes:
- Key Opinion Leader (KOL) Engagements
- Structured interviews with executives, product managers, and domain experts
- Paid and barter-based interviews across manufacturers, distributors, and end-users
- Discussions with stakeholders to validate demand-supply gaps
- Group discussions on emerging technologies, regulatory shifts, and adoption barriers
- Cross-verification of market sizing and forecasts with industry insiders
- Capturing business perspectives on growth opportunities and restraints
Data Triangulation & Forecasting
The final step of our research involves data triangulation ensuring accuracy through cross-verification of:
- Demand-side analysis (consumption patterns, adoption trends, customer spending)
- Supply-side analysis (production, capacity, distribution, and market availability)
- Macroeconomic & microeconomic impact factors
- Time-series analysis
- Regression and correlation studies
- Baseline modeling
- Expert validation at each stage
Outcome
The outcome is a comprehensive and validated market model that captures:
- Market sizing (historical, current, forecast)
- Growth drivers and restraints
- Opportunity mapping and investment hotspots
- Competitive positioning and strategic insights
Our Clients:
