Clinical trial supply management’s future is being shaped.

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Clinical trial supply management’s future is being shaped.

 

The Life Sciences industry’s status quo is being disrupted by the transition of the old pharmaceutical supply chain into a data-driven, patient-centric value chain. ATMPs, or advanced therapy medicinal products, open up new possibilities for tailored treatments including cell and gene therapies. The lines between pharmaceuticals and medical technology are blurring with the introduction of ATMPs and new product and service offerings “beyond the pill,” and pharmaceutical companies must develop a fundamentally different end-to-end capability, focusing on truly patient-centric analysis and response across the entire value chain. From the chemical to the patient, or vein-to-vein, tomorrow’s commercial and clinical value chains will be leaner, faster, more flexible, self-orchestrated, and patient-centric.

The implications for clinical trial procedures are significant. The increasing number of new product launches has an impact on how pharmaceutical companies organize and conduct clinical trials: the number of studies is increasing while trials are shrinking. Due to companion diagnostics, combination products, and longer and more complex production and replenishment procedures, trial designs are becoming more complex. Patient enrollment becomes more competitive as the target population shrinks, the patient and site experience becomes more important, and patients are better informed. Finally, due to an expansion in non-core nations and problems posed by rapidly changing worldwide regulations, pharmaceutical companies are encountering an overall increased level of complexity in the end-to-end trial process.

What role does technology play in this?

The pharmaceutical industry’s evolution is centered on technology. It is transforming healthcare, medical practise, how pharmaceutical breakthroughs reach patients, and how the pharmaceutical business engages with patients. Technology improves the ability of the industry to innovate. We should expect a major rise in the efficiency and effectiveness of the next wave of clinical trials as new technology and real-time data become available. Remote clinical trials, as well as virtual clinical trials in the future, will soon transition from a future trend to a real-life industry standard scenario. The next huge wave of innovation in the Life Sciences business will begin with remote patient monitoring and access to real-time patient data.

Transformational capabilities that are essential

A clinical trial supply management solution should include the following features in order to have a significant impact on future clinical supply processes:

Faster planning cycles and new forms of clinical trial protocol set-ups can be accommodated.

For an end-to-end information flow, harmonize master data and coordinate procedures.

Standardize interfaces to allow for a quicker study start-up while also reducing the operational burden of the clinical supplies system landscape during trial execution.

Be interoperable to enable for system flexibility and expansion, as well as minimal TCO maintenance and updates.

Simply by making study setup easier, good planning is essential for ensuring adequate supply provisioning during a clinical research. CTSM-driven replenishment is based on real-time visibility into actual supply consumption, i.e. anticipating what is needed when and where it is needed, and then procuring, manufacturing, and shipping the required supplies without overproducing or risking supply shortages.

A range of data points must be gathered together in order to plan more accurately:

Enrollment data, both planned and actual
timetables for visits and dispensing,
a study’s or sub-studies’ overall lifespan state,
information on regulatory clearance for the launch of a study or the extension of a shelf life,
stock information in warehouses/depots that is up to date,
in-transit stock, in-transit stock, in-transit stock, in
orders that are currently being processed
and the patient kits’ real-time quality status, particularly in IoT sensor-monitored circumstances.

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