Searching for True End-to-End Clinical Supply Visibility

Article published by Tenthpin Management Consultants in Clinical Trials Arena

With the method of managing the clinical supply chain in clinical trials firmly established through a period of trial and error along with continual adjustment over decades, it is time to take another look at the current paradigm with the new technologies and processes available. Specifically, we will view the growth in understanding for how data integration can bring huge improvements in operational efficiency and lower clinical material waste levels.

One tremendously large area of opportunity for most pharma sponsors is the greater integration of IRT data to achieve near real-time and end-to-end visibility of supply. IRT solutions provide real time information of patient enrolment, drug dispensation, and clinical site supply levels which is gold for understanding how the trial is progressing from a supply chain planning perspective.

What are the challenges in taking this step forward? This article will discuss what events need to take place to enable more data empowered trials to be realised.


What is the current state?

Genuine innovation well beyond current capabilities, i.e., a revolution is required to bring about the capabilities that the industry is crying out for.  

Where are the restrictions? Every organisation has any number of clinical trial solutions which are often old, inflexible, and usually difficult to use, let alone extract meaningful data from. But nonetheless, these solutions and processes manage to survive and become established.

What is needed to gain momentum are the classic stepping stones which form a path to collect data, as simply and efficiently as possible, and deliver it in a meaningful and useful manner.  These are steps that everyone is familiar with, but they are not particularly appealing. On the other hand, the steps are an enabler. Eye-catching results can come later once a base has been established to enable the shiny baubles.


How do we use IRT today?

There are many IRT providers available, most of which offer study IRT build flexibility according to individual study designs and differing supply models. Pharma sponsors tend to align themselves with one or two primary IRT providers, ideally with standards in place to reduce cost and improve repeatability and familiarity.

This standardisation enables data transfers, typically compliance (study conduct) and recruitment information, into a clinical trial management system (CTMS) and clinical supply management system. These are relatively simple but require construction with each IRT provider and any change becomes a large task to align, re-test, and go-live, all while running live studies.

IRT was initially a wholly clinical affair, with all activities performed, and responsibilities remaining with the clinical trial team. As the supply aspect became increasingly important, clinical supply teams have accordingly become more important partners, influencing design and study conduct. This has led to modern IRT platforms having a plethora of settings to achieve very efficient supply chains down to the study site level.


What are the challenges preventing empowerment of available data for greater decision making?


Siloed data and the game changer

A fundamental challenge, and for many a painstaking activity, is to move data between sources, formats, and vendors to create a picture of tactical events at a strategic level to plan and adjust the clinical trial supply chain. For many pharma sponsors the clinical supply study planners can spend as much as 50% of their time gathering data – all done monthly just to execute a plan.

Bringing this data together and in a common set is the goal. With the data captured and available through more automated and standard integrations the effect is dramatic in terms of planning accuracy and frequency, the reduction of clinical supply waste, and in the efficiency and satisfaction of the study planner.


Lack of standards

Aligning data is a fundamental challenge to understand and address. Having IRT data integrated and available in a consistent standard goes a long way to solving this problem without too much additional work. Your data across your IRTs may already be standardised. If not – it should be the very first step, and as a priority.

Standardising your data is not only about synchronisation. There are positive operational impacts; study build becomes less labour intensive, the risk of misinterpretation of core requirements is removed as an issue, and more time is allowed for discussion of customisation needs during the build process.

User experience is also improved with familiarity leading to less effort with data corrections. Your integrated systems will be more likely to have synchronised data as a result, reducing cost in reconciliation.


Data privacy

Sharing data across organisations always comes with strong eCompliance challenges. Drawing off data from an already established (IRT) source has many obvious advantages against creating new data lakes and / or clouds.


A suite of solutions for the clinical trial managers

Lessons learned can often, like non-integrated IRT data, be a siloed experience. The clinical supply study planner will gain experience over time and exposure to differing study designs and roadblocks. The study planner’s performance will of course improve given these (often expensive) learnings.

How do we present and manipulate this data in a simple and repeatable manner? We have seen that often the most effective study planners are those who were most proficient in presenting their data to make experienced decisions. It is a laborious activity, and assuming they will be working on multiple studies, fraught with potential error, affecting decision-making and overall performance.

Study planners should be making informed decisions, not wrestling with data to hopefully provide an overview of the supply situation which becomes out of date almost immediately. Tellingly, the most successful study planners were the best users of Excel.

What we propose is to use the experience and expertise across these integrations with IRT and your supply experts to create uniform reporting tools at a tactical and strategic level to provide assessments through to the end of study.

The potential of a simple aggregated data approach should not be limited to individual studies. Obviously the clearer the picture, the luxury of more time is available to make more informed and confident strategic decisions. Errors and stock-outs should almost become a thing of the past, allowing study planners to manage more trials with less effort and more accuracy.


The outcomes from using centralised IRT data

Looking from a strategic perspective, we will be able to see shipping costs versus quantity shipped in real time. Should we be looking at certain studies to ship fewer but larger shipments? Your dashboard will tell you, with a view of one study, all studies, or perhaps studies in a particular indication. The view can be adjusted as required.

Perhaps most important is that all lessons are captured, and the experience gained can be shared across study planners and clinical supply management.

Feeding into training should also be paramount. If the need for experience can be diminished, then the bar can be raised for all supply planners resulting in efficiencies, role satisfaction, and more time available to focus on process improvements as opposed to fighting fires.


Key Takeaways for the road ahead

The major opportunity of achieving true end-to-end clinical supply visibility can be done by leveraging existing tools rather than building new ones.  The effort is about adapting rather than creating and supplementing an accepted means of operation. With an unclouded vision, the correct tools and expertise deployed on this journey can be made much simpler than has previously been the case. Let us allow our teams to make decisions based on a simple and clear picture and we will reap the tremendous cost, timeframe, and efficiency gains.

Source: ClinicalTrials Arena


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written by

Dan Silva


Iain Little


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