{"id":1400,"date":"2026-07-30T15:24:37","date_gmt":"2026-07-30T13:24:37","guid":{"rendered":"https:\/\/tuneinsight.com\/en\/?p=1400"},"modified":"2026-07-30T15:24:37","modified_gmt":"2026-07-30T13:24:37","slug":"biopharma-data-strategy","status":"publish","type":"post","link":"https:\/\/tuneinsight.com\/en\/news\/data\/biopharma-data-strategy\/","title":{"rendered":"Why biopharma needs to invest massively in data strategy, and why the next 10 years will be pivotal"},"content":{"rendered":"<p><span style=\"font-weight: 400\">Medical research is accelerating at an unprecedented pace. Targeted therapies, immuno-oncology, generative AI, decentralized trials, real-world studies&#8230; Each of these innovations shares a common foundation: data. But this foundation, while essential, remains fragile.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400\">According to WHO, 85% of health data is currently not standardized. And even worse, 97% of data produced in hospitals is never reused, when it could inform research, improve our understanding of diseases, and accelerate access to treatment.<\/span><\/p>\n<p><span style=\"font-weight: 400\">Against this background, investing in a robust data strategy is no longer an option, it\u2019s a necessity for laboratories, biotechs, CROs, medtechs and any Life Science actors that want to survive.<\/span><\/p>\n<h2><b>Without exploitable, continuous data, therapeutic innovation will grind to a halt<\/b><\/h2>\n<p><span style=\"font-weight: 400\">As pathologies become increasingly complex, traditional drug discovery pipeline models (step-by-step, slow, and siloed) simply cannot keep up. Today, Life Science actors must handle massive volumes of data coming from dispersed sources: clinical trials, national registries, imaging, genomics, EHRs, behavioral data, etc.<\/span><\/p>\n<p><span style=\"font-weight: 400\">The shift they are currently facing is the constant intertwining of research, clinical practice and real-world data. A molecule no longer reaches Phase III without being enriched by real-world evidence, and undergoing the kind of iterative analysis needed to adjust cohorts, target sub-populations, and detect unexpected effects.<\/span><\/p>\n<p><span style=\"font-weight: 400\">Yet in practice, R&amp;D and HEOR teams still spend too much of their time on manual tasks: reformatting data, harmonizing heterogeneous databases, waiting for access authorizations, reconstituting dispersed cohorts&#8230;\u00a0 All leading to months of delays, exponential costs, and missed opportunities.<\/span><\/p>\n<p><span style=\"font-weight: 400\">As global competition intensifies, <\/span><b>organizations with the capacity to exploit data faster and more cleanly will gain a decisive scientific advantage.<\/b><\/p>\n<h2><b>Personalized medicine and the need for richer, more detailed, and more granular data<\/b><\/h2>\n<p><span style=\"font-weight: 400\">The surge in personalized treatments\u2014immunotherapies, gene therapies, cell therapies, medications targeting specific mutations, smart combinations\u2014is one of the stand-out transformations of the last decade.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400\">In many cases, these treatments will only help a few hundred or thousand patients per country.\u00a0 To develop them, it is not enough to observe global trends.<\/span><b> An extremely granular approach is required.<\/b><span style=\"font-weight: 400\"> This means combining:<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Clinical data,<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Genomic data,<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Imaging data,<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Care pathway data,<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">And sometimes even behavioral data.<\/span><span style=\"font-weight: 400\"><br \/>\n<\/span><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400\">But this granularity comes with a catch: the different data sources are rarely unified, aligned, or easily shared. They are stuck in technological, regulatory and organizational silos. The biopharma industry must therefore invest in:<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Secure collaborative environments,<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Interoperability standards,<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Analytical capacities that don\u2019t require data transfer,<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Infrastructures that let algorithms move instead of the data.<\/span><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400\">Without this technological leap, personalized medicine remains a pipe dream that is impossible to scale.<\/span><\/p>\n<h2><b>A new European framework: taking data from a scientific regulatory issue to a strategic one<\/b><\/h2>\n<p><span style=\"font-weight: 400\">As the European Health Data Space (EHDS) gains ground and the expectations of regulatory authorities evolve, market access cycles are being reshaped. For laboratories, it\u2019s no longer a question of simply demonstrating that their drugs work. They must also show:<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">The origin and quality of their data,<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">The traceability of their analyses,<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">The conformity of their technical environments,<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">The reproducibility of their models,<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">The robustness of the IA models they use.<\/span><span style=\"font-weight: 400\"><br \/>\n<\/span><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400\">The message is clear: data is no longer a simple research tool. It is also the subject of regulatory oversight, under greater scrutiny than ever before.<\/span><\/p>\n<p><span style=\"font-weight: 400\">With this in mind, actors who shape their data strategy early on will have a clear advantage: less regulatory friction, stronger submissions, faster approvals, and better visibility in market negotiations.<\/span><\/p>\n<p><span style=\"font-weight: 400\">The industry is entering a new era. Data is becoming a regulatory asset, just as valuable as clinical expertise.<\/span><\/p>\n<h2><b>Accessing EU5 data: a major strategic challenge in a highly contrasted global landscape<\/b><\/h2>\n<p><span style=\"font-weight: 400\">The importance of Europe is often overlooked when it comes to data. Yet the EU5 (France, Germany, Italy, Spain, and the UK) in particular represents one of the richest, most complex environments for health data.<\/span><\/p>\n<p><span style=\"font-weight: 400\">This richness is strategic for Life Science actors, as decisions on pricing, reimbursement, and commercial roll-out are all highly dependent on the analysis of local data.<\/span><\/p>\n<p><span style=\"font-weight: 400\">An OECD survey reveals a striking paradox. According to Health Working Paper No. 127 by Jillian Oderkirk (OECD, 2021):<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">The USA is among the countries with the most well-structured governance of health data, thanks in particular to a strong push to make data available for research.<\/span><span style=\"font-weight: 400\"><br \/>\n<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Yet it only has 54% of the datasets recommended by the OECD, behind Korea and France with more than 90%.<\/span><span style=\"font-weight: 400\"><br \/>\n<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">And despite this relative fragmentation, the USA counts the highest number of health data start-ups and unicorns.<\/span><span style=\"font-weight: 400\"><br \/>\n<\/span><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400\">It\u2019s a fascinating observation: the USA doesn\u2019t necessarily offer the best data access, but it has built the most dynamic innovation ecosystem. Europe, by contrast, has a colossal wealth of data (particularly in France, where data structure is recognized as among the best in the OECD), but still struggles to mobilize it.<\/span><\/p>\n<p><span style=\"font-weight: 400\">For Life Science actors, the opportunity is enormous: harnessing, harmonizing, and exploiting EU5 data represents a decisive competitive advantage. Securing an accurate view of healthcare practice, patient pathways, sub-populations, and therapeutic performance in Europe can:<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Ensure the success of a launch,<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Guide HEOR strategy,<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Strengthen payer negotiations,<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Instruct priority country selection,<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Cement clinical investment decisions.<\/span><span style=\"font-weight: 400\"><br \/>\n<\/span><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400\">Over the next ten years, laboratories with the capacity to leverage European data will gain a considerable lead, both scientifically and commercially.<\/span><\/p>\n<p><span style=\"font-weight: 400\">Innovation no longer relies on science alone: it depends on the capacity to mobilize, protect, connect, and exploit data without friction. Life Science actors who invest in their data strategy today are not only securing their success for tomorrow, they are positioning themselves as those who will set the benchmark for the industry as a whole.<\/span><\/p>\n<p>&nbsp;<\/p>\n<p><span style=\"font-weight: 400\">Sources: EHDS (COM\/2022\/197), EMA (RWE 2022; AI 2023), EUnetHTA 21, OECD Health Working Paper 127, NIS2 Directive (2022\/2555), GDPR (2016\/679).<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Medical research is accelerating at an unprecedented pace. Targeted therapies, immuno-oncology, generative AI, decentralized trials, real-world studies&#8230; Each of these innovations shares a common foundation: data. But this foundation, while&#8230;<\/p>\n","protected":false},"author":2,"featured_media":1401,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"inline_featured_image":false,"footnotes":""},"categories":[7],"tags":[],"class_list":["post-1400","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-data"],"acf":[],"_links":{"self":[{"href":"https:\/\/tuneinsight.com\/en\/wp-json\/wp\/v2\/posts\/1400","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/tuneinsight.com\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/tuneinsight.com\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/tuneinsight.com\/en\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/tuneinsight.com\/en\/wp-json\/wp\/v2\/comments?post=1400"}],"version-history":[{"count":3,"href":"https:\/\/tuneinsight.com\/en\/wp-json\/wp\/v2\/posts\/1400\/revisions"}],"predecessor-version":[{"id":1404,"href":"https:\/\/tuneinsight.com\/en\/wp-json\/wp\/v2\/posts\/1400\/revisions\/1404"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/tuneinsight.com\/en\/wp-json\/wp\/v2\/media\/1401"}],"wp:attachment":[{"href":"https:\/\/tuneinsight.com\/en\/wp-json\/wp\/v2\/media?parent=1400"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/tuneinsight.com\/en\/wp-json\/wp\/v2\/categories?post=1400"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/tuneinsight.com\/en\/wp-json\/wp\/v2\/tags?post=1400"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}