Key Points
  • Speed-to-insight is key to making the best decisions at the right time in a highly competitive pharmaceutical industry

  • Competitive Intelligence (CI) solutions, embedded with artificial Intelligence and machine learning, help pharma companies to quickly identify opportunities for innovation from diverse data sources

  • Leveraging advanced CI solutions, pharma companies can better prioritize research and development spend, reduce effort and accelerate time-to-market

On an average it takes USD 2 Billion, and 10 to 12 years to release a drug into the market. Of the drugs that enter the clinical trial phase in the US, only 10 percent gain approval for patient usage. Tens of thousands of candidate drugs fail to enter production in any given year, costing pharmaceutical companies millions of dollars. This makes optimal decision-making the most important challenge for pharmaceutical companies in a highly uncertain landscape.

Speed-to-insight is crucial to achieve the best outcomes across time-to-market, product development, portfolio management, pricing and brand positioning. In the absence of an intelligent, collaborative platform to find, organize, analyze and prioritize structured and unstructured data, insights that are generated can sometimes be counter-productive.

This is where data and analytics-powered Competitive Intelligence (CI) solutions, underpinned by technologies such as Artificial Intelligence (AI) and Machine Learning (ML), become an imperative for pharma companies. Globally, the AI market for the pharma industry is expected to touch USD 8.15 Billion by the end of 2026.

AI and ML-based CI solutions help in quickly and efficiently identifying new opportunities from diverse data sources, and enable decision-makers to prioritize the right product pipelines for innovation.

AI and ML ensure that only qualified data from standard sources is analyzed, and also help in comparing data in different formats to quickly arrive at actionable insights. CI solutions embedded with these technologies help spot anomalies swiftly and expose questionable patterns, thus improving the quality of the insights delivered. Self-learning algorithms behind sophisticated CI solutions can trace and reduce potential sources of biases in data. When complemented with deep domain knowledge, these solutions help in refining the insights further by leveraging human reasoning.

Insights to Innovation: Joining the Dots

An effective analytics-led pharma CI platform can ease the process of delivering insights through data visualization, dynamic dashboards and intelligent recommendations.

Here are a few ways in which a CI platform that supports speed-to-insight delivers value to pharma companies:

  • Improved Prioritization of Research and Development (R&D) Spend: Timely updates on the competitive landscape enable companies to allocate the right funds and resources for the right product. System-based predictions of drug interactions and accurate forecasts help in planning and optimizing R&D spend more efficiently, while curtailing losses

  • Reduced Effort in the Development of Medicines: When delivered as a cloud-based solution, a CI platform breaks down information silos and facilitates seamless, real-time collaboration among distributed teams to reduce effort and accelerate speed-to-insight in drug development and marketing

  • Accelerated Time-to-Market: The right market intelligence from an advanced CI solution can help pharma companies seize opportunities quickly, while improving business agility to create a first-mover advantage in a competitive marketplace

Strategic decision-making in the pharma industry has long moved away from assumptions based on historical data or experience. Real-time assessments and information, and intelligent predictive capabilities are key to reduce time-to-market and spark genuine innovation thus making an advanced CI platform crucial to pharma success today.

   

Know more about WNS Precizon, an AI-led CI solution for the pharma industry

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