Unless the pharmaceutical industry manages product lifecycle data holistically in 2016, companies’ ability to achieve regulatory compliance and maintain speed to market will be compromised, warns Mark Evenepoel, Group, Amplexor Life Sciences
Of all the challenges facing life sciences organisations in 2016, it is the conflicting priorities of regulatory compliance and global competitive pressure that will be the most demanding. That’s unless companies find a new, more holistic way to manage their product lifecycle data right across their operations – from R&D to market distribution.
Without a single, master approach to data, a company’s ability to seize new opportunities will be limited by the substantial administrative burden associated with meeting the growing number of regulatory requirements in each target market. In an aggressive global playing field, success relies on speed and adaptability which is difficult to maintain against a flow of red tape.
2016 will be a turning point, for a number of reasons. Data silos – so common in pharma due to the global sprawl of companies and the industry’s history of merger and acquisition – are a barrier to agility. They result in administrative repetition, they incur inaccuracy, and they compromise the ability to deliver correct content quickly to where it’s needed to get a product to market promptly.
Preparing for regulatory requirements – current & future
Managing fragmented data systems and processes is expensive. According to research published by Gens & Associates in April 2015, life sciences organisations that manage their content at a holistic, pan-enterprise level see better ROI than those persisting with standalone projects.
Yet the temptation to approach product data management on a project by project basis remains. New EU legislation requires the implementation of new data standards (Identification of Medicinal Products or IDMP) – designed to enable the unique identification of medicinal products at an international level. To comply, life sciences organisations must develop a method and process for generating global product identifiers, which can then be used for product reconciliation and linking across the entire product supply chain.
Significant investment will be required not only to align key product data across a range of functions, also to pursue operational excellence in R&D and customer safety: the ultimate goal of the new standards. From a regulatory and risk perspective, these requirements absolutely must be met. But companies need to do this in a way that is both efficient and adaptable – as new regulatory requirements will continue to appear and evolve, and not all of these can be predicted in advance.
Supporting new product strategies
At the same time, companies must raise their game commercially. The last year has seen considerable strategic change in the life sciences industry, as pharma organisations have sought to realign their value propositions with target customer groups. Selling solutions rather than product features is not only more appealing to customers, it also presents additional cross-selling opportunities.
But again, all of this is difficult to manage optimally with a single set of supporting data, and robust processes that will enable this new way of promoting products. New strategies must involve strengthening collaboration and information-sharing - both among internal functions and with external partners - to create a global supply ecosystem that is more closely integrated, responsive and focused on the patient. And this must begin with a single, centralised approach to product lifecycle data management.
Developing a plan
Rather than bemoan the issues, companies need to take assertive action so that 2016 is a transformational year. The first objective must be to design a clear roadmap for a centralised approach to produce lifecycle data management. Even where legacy systems are an important consideration, organisations should work towards a centralised strategy for master data and product lifecycle information management. This could be achieved virtually, for example, but external experts can be called upon to help with the ‘how’.
There is light at the end of the tunnel. Pharma companies are already sitting on most of the data they need to achieve their goals (albeit not necessarily in a structured format yet), because of the regulatory demand to capture and document high levels of detail. The opportunity now is to unlock, structure and amalgamate this data so that it can be exploited to competitive advantage.