In the era of globalisation the supply chains were severely skewed in favour of low-cost manufacturing hubs. For instance, a majority of active ingredients manufacturing was concentrated in 3 to 4 locations. The recent geopolitical dynamics (including the pandemic) exposed severe dependencies resulting in shortages. 

As we delve into 2024, these elements converge to create a challenging landscape for the production, distribution, and procurement of essential medical supplies. Here’s an expanded look at the multifaceted impact these global dynamics are having on the medical supply chain.

Geopolitical Disruptions and Strategic Realignment

Recent geopolitical events have prompted significant strategic realignments within global supply chains. The Russian invasion of Ukraine has not only led to immediate disruptions but also long-term rethinking of supply chain dependencies. 

For example, the conflict has jeopardised the supply of noble gases critical for semiconductor manufacturing, a vital component in numerous medical devices.

Moreover, the ongoing U.S.-China trade tensions exacerbate the situation, as these two economic giants grapple with issues ranging from tariffs to technology transfer restrictions. 

The result is a medical supply chain caught in the crossfire, facing increased costs and potential delays in the delivery of critical goods.

In brief

• Pharmaceutical companies are facing major headwinds due to loss of exclusivity (LOE) as product patents are set to expire, with billions in sales at stake.
• While sunsetting products is not new, maximising value in today’s environment requires a strategic approach.
• Savvy industry leaders are aligning sales, marketing, legal and other functions to reduce costs and drive value at the end of a product’s lifecycle.

Introduction

When a new prescription drug is launched, the pharmaceutical innovator holds exclusive rights to develop, sell, and market the drug during the patent period, typically lasting 10 to 15 years. After this period, the brand faces loss of exclusivity (LOE), relinquishing its monopoly and preparing for the entry of lower-cost generic (Gx) alternatives. This significant milestone requires a comprehensive adjustment in brand strategy.

Defensive strategies, such as intellectual property (IP) litigations and patent extensions, are often the first recourse prior to LOE. However, once these legal options are exhausted, the impact of Gx entry on sales volume can be immediate and substantial. To mitigate this, companies can maximise the revenue potential of the brand through line extensions and leveraging brand loyalty.

This necessitates strategic planning around commercial priorities and close coordination with other functions, akin to the launch phase of the drug. When extracting further value from the brand is no longer viable, companies typically switch patients to next-generation or over-the-counter (OTC) products, gradually sunsetting the original brand.

As a pharmaceutical company approaches the LOE, it must also navigate a highly competitive landscape where market dynamics rapidly shift in favour of cost-effective alternatives. This transition phase demands a proactive approach, integrating market access strategies with advanced analytics to anticipate and respond to competitive pressures.

Understanding prescriber behaviour, payer influence, and patient adherence becomes critical in retaining market share. Moreover, effective communication with healthcare providers and stakeholders is essential to maintain the brand’s value proposition during this pivotal period.

Introduction

The European Federation of Pharmaceutical Industries and Associations (EFPIA) has recently published a white paper addressing key challenges in medicine procurement within the EU and UK. This white paper emphasises the need for effective and sustainable procurement practices that can deliver high-quality medicines to patients in appropriate quantities and at the right time.

Background on Tendering Practices

Tendering processes in pharmaceuticals play a crucial role in determining how medicines are procured and distributed. These processes, however, have been plagued by various issues that affect competition and limit access to essential medications. A recent EFPIA survey highlighted seven anomalies in national tendering practices in the EU & UK that harm competition and potentially limit patients’ access to medicines.

EFPIA’s White Paper Overview

EFPIA’s white paper, published on February 10, 2022, presents a sector-specific contribution to the broader debate on the efficacy of the EU procurement rules. It aims to improve not only the formal public procurement procedures but also the informal tendering processes increasingly employed outside the confines of Directive 2014/24/EU.

The Ten Recommendations

1.Transparency in Procurement Processes: Advocates for clearer and more open procedures to enhance fairness.
2. Balancing Cost with Quality: Proposes evaluating tenders based on both price and quality.
3. Long-Term Agreements: Suggests longer contracts to ensure stable supply and predictability for manufacturers.
4. Risk Mitigation Strategies: Recommends measures to prevent drug shortages, including contingency plans.
5. Incentivising Innovation: Encourages mechanisms to reward and promote the development of new treatments.
6. Sustainable Pricing Models: Calls for pricing that reflects the value of medicines while ensuring accessibility.
7. Collaboration with Stakeholders: Stresses the importance of involving all relevant parties in the procurement process.
8. Flexibility in Contracts: Advises adapting contracts as new treatments become available or needs change.
9. Streamlined Administrative Processes: Recommends reducing bureaucracy in the procurement process.
10. Regular Monitoring and Review: Urges ongoing assessment of procurement practices for effectiveness.

Expanded Insights

EFPIA’s recommendations focus on three distinct types of public procurement rules and practices. These include traditional EU public procurement rules, the 2014 Joint Procurement Agreement, and informal tendering processes. The recommendations seek to enhance efficiency, bolster fair competition, and address flaws revealed in market feedback obtained from a survey of tendering practices in 18 countries across the EU and the UK.

Impact on Healthcare and Industry

Implementing these recommendations could lead to more affordable medication prices, fostering accessibility and stimulating growth in the pharmaceutical sector. Furthermore, encouraging innovation could result in the development of new, more effective treatments, significantly improving patient outcomes.

Conclusion

EFPIA’s recommendations offer a roadmap for enhancing medicine procurement practices in the EU and UK, aiming to improve access to quality medicines and foster a more dynamic pharmaceutical sector. While challenges in implementation exist, the potential benefits for healthcare delivery and industry growth are substantial.

In this context, platforms like Vamstar’s could play a crucial role. Vamstar, with its advanced digital procurement solutions, can support the adoption of these recommendations by providing a more efficient, transparent, and data-driven approach to procurement. Its technology could facilitate better collaboration among stakeholders, streamline the procurement process, and offer insights into market trends and supplier performance.

This aligns perfectly with EFPIA’s call for improved procedures and increased transparency in the tendering process. By leveraging such innovative platforms, stakeholders can work together more effectively to ensure a healthcare system that not only meets the needs of its patients but also aligns with the resilience and growth goals of the EU.

In the complex and fast-evolving landscape of global markets, the strategic importance of pricing can hardly be overstated. It’s the linchpin that not only affects revenue and margins but also determines market competitiveness.

This is where Artificial Intelligence (AI) steps in, revolutionising the way industries approach pricing strategies. In particular, the implementation of AI in tender and RFP (Request for Proposal) pricing across Italy, Spain, France, the Nordics, and other EU & ME markets has been nothing short of transformative.

The AI-Driven Pricing Revolution

AI technology has opened new avenues for analysing historical data, recognising patterns of wins and losses, and applying these insights to future tenders and RFPs. This analytical prowess has empowered businesses with predictions and scenarios rooted in real-life outcomes, leading to substantial revenue growth — ranging from 12% to 25% — and enhanced margins by 17% to 25% across diverse markets and assets.

Our Three-Phased Approach to Pricing

Our journey towards pricing is meticulously structured into three phases, each designed to build upon the insights and foundations laid in the preceding steps.

Phase 1: Data Discovery, Cleansing, and Enrichment

The first step in the process is to meticulously curate and enhance the dataset, ensuring its integrity and richness. This involves a thorough examination of the data to identify any inconsistencies, errors, or missing information that could potentially undermine the accuracy of the predictive models. Once these issues are detected, the data undergoes a rigorous cleansing process to correct the invalid entries and ensure the dataset’s overall quality.

However, the preparation phase goes beyond mere data cleaning. To truly unlock the potential of the predictive models, it is essential to enrich the dataset with valuable market insights. This enrichment process involves integrating relevant external data sources, such as industry trends, competitive intelligence, and regulatory information, to provide a more comprehensive and contextual understanding of the market dynamics.

By combining the internal data with these external insights, the dataset becomes a powerful asset that can drive more accurate and actionable predictions. This solid foundation of clean, enriched data sets the stage for the development of robust and reliable predictive models in the subsequent phases of the project.

Phase 2: Model Building

In this phase, the focus is on developing sophisticated predictive models that incorporate a vast array of variables. These models are designed to tackle complex challenges, such as forecasting prices at the molecular level and identifying the most likely winning bids for individual stock-keeping units (SKUs).

The algorithms take into account a wide range of factors that influence the pricing of drugs or medical products throughout their entire lifecycle, from initial launch to post-patent expiry scenarios. By considering the impact of various market dynamics, regulatory changes, and competitive landscapes, these models provide valuable insights into pricing strategies and help organisations navigate the complexities of the pharmaceutical and healthcare industries. The ultimate goal is to empower local teams with data-driven recommendations that optimise revenue, maximise profitability, and ensure sustainable growth in an increasingly competitive market.

Phase 3: Iterative optimisation through A/B testing and reinforcement learning

In the final phase of the project, a two-pronged approach will be used to refine and validate the effectiveness of our pricing pilot. First, extensive A/B testing will be conducted, comparing the performance of our AI-driven pricing strategies with traditional methods. This rigorous benchmarking process will allow us to quantify the concrete improvements and added value brought by the new solution. By measuring key metrics such as revenue growth, margin expansion, and market share gains, the model simulates real-world scenarios.

However, for a continuous learning process, we harness the power of reinforcement learning to create a self-optimising feedback loop. Because Pricing Co-Pilot is deployed under real market conditions, it actively learns from the results of its decisions. By analysing real-world results, the machine learning algorithms identify patterns, correlations, and causal relationships between different factors and their impact on pricing effectiveness. This ongoing learning process allows the models to adapt and refine their predictions over time, becoming increasingly accurate and responsive to changing market dynamics.

One of the key benefits of this iterative optimisation approach is the ability to simulate a variety of scenarios. Leveraging the advanced models, teams can explore different pricing strategies, campaigns, and competitive responses in a virtual environment. This allows them to evaluate the potential outcomes and risks associated with each scenario and empowers them to make informed decisions based on data-driven insights.

By combining A/B testing and reinforcement learning, the Pricing Co-Pilot aims to achieve continuous evolution and adaptation to the ever-changing landscape of the pharmaceutical and medical device industries. This phase serves as the foundation for the project, delivering a robust, reliable, and continuously improved pricing solution that drives sustainable growth and profitability.

The Vamstar Difference

The drive for greater commercial efficiency has become increasingly urgent against a backdrop of inflation, shortages, and the shift towards value-based healthcare. Vamstar distinguishes itself by leveraging AI to orchestrate, analyse, and provide intelligence on MedTech and Pharmaceutical data. This approach not only enhances market visibility but also optimises pricing strategies, thereby simplifying and automating commercial workflows to achieve sales excellence.

The Impact

Adopting AI in pricing does more than just improve financial metrics; it represents a paradigm shift in how businesses approach the market. By providing a granular view of demand and supply dynamics, and facilitating informed decision-making, AI technologies like those offered by Pricing Co-Pilot are setting new standards for efficiency and competitiveness in the healthcare sector.

Conclusion

The integration of AI into pricing strategies marks a significant leap forward for industries striving to navigate the complexities of modern markets. With its proven track record of enhancing revenues and margins, AI offers a promising path to not just survive but thrive in the competitive landscape. As we continue to explore and refine these technologies, the possibilities for innovation and improvement in pricing strategies are boundless.