The pharmaceutical industry is on the verge of transformation with purpose-built artificial intelligence (AI) solutions. Top artificial intelligence consulting firms help top pharma players identify market gaps with the power of data. These consulting firms enable key players to rethink their data strategies to create competitive differentiation. It is a solid move towards building an “economic moat” with continuous learning and adaptability.

Where does data create unique value in the pharma industry?

Finding existing challenges

The pharmaceutical and life sciences sector has relied on traditional data sources for the longest time. Each business domain in pharmaceutical companies utilizes vast sets of data. From research and manufacturing to marketing and distribution, data is the core of building a successful drug or treatment. The limitation comes from using the same data set without leveraging third-party syndicated data. It burdens the overall system, leading to inefficiencies and delays in drug development, market access planning, and distribution models.

What are the solutions by consulting firms using AI?

Novel solutions with multi-model data

Consulting firms offer strategic advice on creating novel solutions using multi-model data. AI has transformative capabilities in market research. Pharmaceutical companies can use intelligent AI models to combine structured and unstructured data to create meaningful metadata. It can be easily transferred across teams to improve organizational outcomes. Multi-model data changes the way organizations collect, collate, format, and access data, which can bring a huge change in the R&D infrastructure.

Building search capabilities

Stakeholders must have advanced search capabilities when dealing with a large volume of data. Even if the data exists, it requires certain efforts to access the right data at the right stage of drug development, marketing, or distribution. Business technology consulting amalgamates organizational processes to enhance search capabilities. They bring in the concept of generative AI agents and agentic workflows to automate data creation, collection, and accessibility. Pharma companies employ an AI-powered answer engine that understands human language context. These technologies can answer natural language queries with complete ease.

How to determine a purpose-built data strategy?

Pay attention to data uniqueness

When leveraging data, it is essential to understand its uniqueness, accessibility, and novelty. A unique data set gives a competitive advantage as it is not readily available to competitors. Some of the unique data include clinical trial data and patient reports. These proprietary data are exclusively available to the pharmaceutical company. This creates a differentiation in the market positioning and is also handy in the unique value proposition.

Adopt an agile approach

Most organizations that depend on three-to-five-year data planning must adopt an agile model. This model enables data collection, connection, and enrichment dynamically. It is surely a step above the traditional data management approach for various enterprise processes. Real-time data streams empower pharmaceutical organizations for better decision-making and market responsiveness.

Use a combination of data

A robust data system using first-, second-, and third-party data is the best that an organization can do. It is a long-term strategic move to strengthen and streamline the pharmaceutical processes.

Leading consulting firms provide purpose-built AI solutions to improve healthcare ecosystem engagement, manufacturing optimization using predictive data analysis, and utilization of commercial data for better contextualization. Its application is dynamic, making it a big move to improve the overall pharmaceutical landscape.