Massimo Crudeli
With a precision medical revolution underway, pharma and biotech firms must take a new look at processes and workflows around data collection, data analysis, and manufacturing.
While traditional drug development has done wonders for humanity, drugs formulated for average patient populations aren’t always safe or effective for specific individuals. The top ten highest-grossing drugs in the United States, for example, only benefit between 4% and 25% of the patients who take them.
Advances in pharmacogenomics — how different people react to medicines — are helping the healthcare industry move away from “one-size-fits-all” drugs. By studying DNA and other information, scientists can determine what medicines may be dangerous — or completely ineffective — for particular people.
Personalized or precision medicine is changing current drug development and manufacturing paradigms in pursuit of individualized treatments. At the heart of the new paradigm is the collection and analysis of “omics” data—genomics, proteomics, epigenomics, transcriptomics, metabolomics, and more—that can help identify molecular factors and biomarkers that drive disease and predict therapy effectiveness.
Digital Transformation Is Transforming Drug Development
The digital transformation of the healthcare industry is the foundation upon which precision medicine rests:
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Advances in biomarker testing and DNA sequencing are improving patient selection.
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Artificial Intelligence (AI) is accelerating drug commercialization.
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Robotics, cloud, Internet of Things (IoT), and other technologies are improving the quality and efficiency of manufacturing complex drugs, such as cell and gene therapies.
Creating precision medicines requires a whole new set of data points, processes, and workflows. Clinical trials, for example, focus on individual patients instead of groups, and rely on the frequent collection and aggregation of clinical information and biological data.
And instead of manufacturing, storing, and distributing multiple lots of medicine for entire populations, more drugs are being 3D-printed in real time, based on individualized prescriptions.
Looking at the big picture, modern biomedical science is guided by four interrelated pillars:
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Personalized medicine
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Data-intensive assays, such as DNA sequencing, proteomics, imaging protocols, and wireless health monitoring devices
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Research that aggregates massive amounts of data from different sources
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Artificial Intelligence to facilitate data analysis
How Life Sciences Organizations Can Rise to the Moment
The key for successful drug development moving forward will be the ability to bring these four pillars together for seamless transitions between diagnosis, treatment, and follow-up monitoring of individual patients. Warehousing the results of N-of-1 clinical trials in accessible databases is also critical, so insights from individual patients can help larger groups of people with similar characteristics.
The first step in facilitating these efforts is for pharmaceutical companies, biotech firms, and their CMO/CDMO partners to get a better handle on collecting, organizing, storing, harmonizing, and interpreting relevant data, through an Enterprise Resource Planning (ERP) system with foundational AI capabilities.
Many life sciences organizations are using outdated ERP systems.
Talk to STAEDEAN about digitalizing your company today for
greater efficiency and cost savings.
This is available today in a solution that combines Microsoft Dynamics 365, the Microsoft 365 Copilot AI assistant, and configurable life sciences solutions from STAEDEAN that facilitate Pharma Supply Chain Management, Advanced Quality Management, Clinical Supplies, and other key drug development processes.
STAEDEAN Life Sciences Solution Is the Most Complete ERP Solution for Life Sciences
Convenient, configurable ERP solutions are purpose-built for life sciences organizations. These solutions can be added as needed, making it easy to scale the solution so it grows with your specific needs.
STAEDEAN's plug-and-play solutions are specifically designed to help life sciences organizations automate workflows, collect relevant data in the correct formats, and conform to standards and regulations such as GMP, GAMP5, FDA 21 CFR Part 11, and EU Annex 11.
Learn how you can increase digital plant maturity and embrace innovations in drug and medical device manufacturing
Massimo Crudeli