AI-Powered Market Intelligence Tools in Pharma and Life Sciences

Data is the new currency for biopharma and life sciences companies, but it’s also a source of complexity and inefficiency. Currently, these industries are facing unprecedented challenges around data mining and interoperability. How can these companies harness the power of AI-driven market intelligence tools to transform their data into insights and actions that drive innovation and value?

Let’s explore some of the key issues facing industry professionals, examples of how AI can help overcome these challenges, and an in-market, battle-tested solution available to enable AI adoption. 

Market Intelligence Data Challenges for Pharma and Life Sciences

The pharma and life sciences industries generate and consume massive amounts of data from various sources, including:

• Clinical trials
• Electronic health records
• Genomic sequencing
• Scientific literature
• Patents
• Regulatory documents
• Market research
• Social media, etc.

However, this data is often siloed, unstructured, incomplete, inconsistent or outdated, making it hard to access and analyze across the organization. These data challenges can hinder pharma and life sciences processes across the value chain.

Here are some of the areas in this industry that are hampered by the inefficient use of market intelligence:

Drug Discovery

Finding novel targets and compounds relevant to a specific disease or patient population can be difficult due to the vast amount of scientific data available and the complexity of biological systems.

Clinical Trials

It may be challenging to design and conduct efficient and effective trials that meet regulatory standards and patient needs due to the variability of patient populations and outcomes across different regions and settings.

Operations

Professionals may encounter difficulties when optimizing the supply chain and manufacturing processes that ensure the quality, safety and availability of drugs due to the variability of demand, supply and environmental factors across different markets and locations.

Commerce and Marketing

Without proper consumer analysis, it’s difficult to personalize engagement with healthcare professionals, patients and other stakeholders because of the diversity of preferences and behaviors across different segments and channels. 

How Market Intelligence Tools Work

By leveraging advanced technologies, such as artificial intelligence (AI) and data analytics, these tools usually share the following steps in providing market intelligence:

1. Data collection: Data is gathered from diverse sources, including public databases, industry reports, social media, news articles and proprietary databases. Different types of tools, tailored for specific purposes like competitive intelligence or social media monitoring, extract insights from distinct sets of sources, further enriching the depth and breadth of gathered information.

2. Data analysis: The tools utilize AI algorithms and analytics techniques to process and analyze the collected data. This involves identifying patterns, trends, correlations and anomalies within the data. Automated data collection and analysis reduce manual effort — saving time, improving efficiency and increasing productivity by allowing teams to focus on higher-value tasks.

3. Insight generation: Based on the analyzed data, the tools generate observations and valuable information about market dynamics, consumer behavior, competitor activities and industry trends. 

4. Report generation: These AI-powered tools produce comprehensive reports that summarize the key findings, insights and recommendations based on the analyzed data. These reports help stakeholders understand the market landscape and make informed decisions.

5. Real-time monitoring: Some tools offer features for real-time monitoring of market conditions, competitor activities and industry trends. This allows organizations to stay updated and make timely decisions.

6. Decision-making support: These tools assist organizations in making strategic decisions by providing actionable recommendations, identifying market opportunities and mitigating risks.

7. Mitigation of Risks and Challenges: AI-powered tools monitor regulatory changes, analyze their impact and provide compliance insights. They also identify risks such as safety concerns, competitive threats or market disruptions, enabling proactive measures to be taken.

How Can Market Intelligence Tools Help Biopharma and Life Sciences?

By harnessing the power of AI and advanced analytics, organizations in the biopharma sector can gain an edge. Market intelligence tools can help in almost every area of these industries:

Research and Development (R&D)

An AI-driven market intelligence tool can help biopharma companies to identify emerging industry trends, predict disease prevalence and uncover potential therapeutic targets. By analyzing vast amounts of data from diverse sources such as scientific literature, clinical trials and patient data, AI can accelerate the drug discovery process and enhance the success rate of clinical trials. This has the potential to significantly reduce costs and time-to-market for new treatments.

Marketing and Sales

Competitive intelligence provides valuable insights into customer behavior, market trends and the competitive landscape. By leveraging AI algorithms, biopharma companies can analyze large volumes of data from multiple channels, including social media, electronic health records and sales data, to understand customer preferences, personalize marketing campaigns and optimize sales strategies and marketing efforts. This consumer intelligence enables companies to target the right audience, tailor messaging and enhance customer engagement.

Supply Chain and Operations

Market intelligence tools can optimize inventory management, demand forecasting and distribution logistics. By integrating data from disparate data sources, including suppliers, manufacturers and distributors, AI algorithms can identify patterns, anticipate demand fluctuations and optimize inventory levels. This reduces waste, improves efficiency and ensures the timely delivery of critical medicines to patients.

Regulatory Compliance

By monitoring and analyzing vast amounts of data related to safety, efficacy and adverse events, AI-driven market intelligence also supports regulatory compliance. This helps biopharma companies stay updated with changing regulations, detect potential risks and ensure compliance throughout the product lifecycle.

Drug Safety

Market intelligence tools extract valuable patient and HCP insights for product development. They mine diverse sources like complaints, inquiries and social media to capture the "voice" of these stakeholders. These insights, when combined with AI-generated data, revolutionize decision-making across the value chain.

AI streamlines drug safety by automating adverse event processing, cutting costs, enhancing case quality, prioritizing resources and ensuring compliance. Case studies highlight AI's role in boosting patient safety, compliance and overall efficiency.

Challenges and Limitations of Market Intelligence Tools

AI-powered market intelligence tools bring immense benefits, yet acknowledging and mitigating their challenges is crucial. Consider these key points:

Data Quality and Availability 

Reliably sourcing comprehensive data, especially in regulated fields like pharma, can be challenging due to gaps, biases and privacy concerns.

AI Algorithm Interpretability and Explainability

Understanding AI-generated results, particularly in regulated industries, is complex. Transparent and explainable outcomes are crucial for clear reasoning.

Regulatory and Ethical Compliance

Adhering to legal frameworks, including patient privacy and data security, is paramount in fields like pharma and life sciences, necessitating proactive measures.

Human Expertise and Judgment

While AI offers valuable insights, it should augment human expertise, particularly in specialized domains. Domain knowledge is essential for contextual understanding and validating AI-generated insights.

InfoNgen, a Market Intelligence Tool to Support Pharma & Life Sciences

InfoNgen, a text analytics software developed by EPAM, provides valuable insights by curating data in a way that drives better decision-making and innovation.

Use Case 1: Improving Enterprise Content Aggregation, Search and Alerting

Customer Problem: A global healthcare company faced challenges in efficiently aggregating and delivering insights from various sources, including medical journals, business news and web content. They sought an enterprise knowledge and alerting portal to streamline content aggregation, enhance search efficiency and provide relevant information to their stakeholders.

Solution Proposed: To address these challenges, the company implemented the out-of-the-box InfoNgen web portal and mobile apps.

This solution integrated over 3,000 subscription sources and enabled efficient content search, automated alerting and curated newsletters. InfoNgen's text analytics capabilities facilitated accurate searches across diverse content sources, such as medical journals, patents, business news, industry publications, clinical trials, newsletters and social media.

Results Achieved: Following the implementation of InfoNgen, the healthcare company achieved remarkable outcomes:

• Over 8,000 users were registered and 25,000 daily email deliverables were produced
• More than 50% reported time saved compared to the previous solution, as users found relevant content more efficiently
• The automated alerting feature enabled users to self-select relevant subjects and publications for notifications, ensuring stakeholders stay up to date on important matters 
• With curated newsletters, power users created detailed digests covering specific subjects, with multiple publishing workflows and personalized insights

Use Case 2: Enhancing Supply Chain Efficiency and Forecasting Accuracy

Customer Problem: A well-known pharmaceutical distribution and health information technology company faced challenges in managing its supply chain and assessing risks associated with its vendors. The sheer volume of data and the need for timely insights made it difficult for the client to effectively forecast product demand and optimize their supply chain operations.

Solution Proposed: To address these challenges, the client utilized EPAM's market intelligence tool, InfoNgen, in conjunction with Google's Data Signals, to develop a supply chain and risk assessment dashboard. InfoNgen's advanced analytics and data processing capabilities allowed for comprehensive data analysis and insights generation.

Results Achieved: Through the use of the supply chain and risk assessment dashboard powered by InfoNgen, the client achieved significant improvements in their product forecasts. Out of 30,000 product forecasts, InfoNgen improved 10,027 forecasts, which led to outperforming the client's baseline forecasts by more than 2 percentage points.

Conclusion

AI-powered tools will revolutionize pharma and life sciences, enhancing all value stream aspects. They offer real-time market insights, process optimization and personalization — fostering innovation, superior products and enhanced patient care. AI-driven market intelligence isn't a distant vision but a present force already shaping the future.