The World Health Organization declared the Covid-19 crisis to be a pandemic in mid-March 2020. Nine months later, three vaccines were approved and commercialised for Covid-19 in various countries across the world: AstraZeneca/University of Oxford’s adenovirus candidate, Pfizer/BioNTech’s mRNA vaccine and another mRNA candidate made by Moderna.
Being able to develop and bring a drug to market in less than a year is an unprecedented feat; it usually takes an average of ten years. How did these three companies and their partners manage to develop vaccines from scratch and carry out large-scale clinical trials so quickly to bring Covid-19 vaccines to the market in record time?
Clinical trial supply management company N-SIDE life sciences director Sébastien Coppe discusses the role digitisation played in clinical success in the pandemic, and how embracing technology can optimise clinical trials in the future.
Allie Nawrat: What are the main bottlenecks in drug development and clinical trials? How can digitisation help to overcome these challenges?
Sébastien Coppe: The main traditional bottleneck is often coming from manufacturing. Covid-19 vaccines have already been commercialised for a couple of months, but you hear about the limited manufacturing capabilities.
When you have a limited amount of capability available you need to know when and how to liberate it. That is where technology and digitisation can help to really streamline all the different stakeholders to try and reduce these bottlenecks and to make sure you can maximise the use of the limited amount of manufacturing capability.
When speaking about technology, optimisation is the most important [element]. You need to optimise all the different steps – and there are lots of steps – to make sure all the stakeholders are aligned. It involves two different things: optimising each single decision and making sure there is alignment to connect the dots between all the different stakeholders. [There needs to be] a triangle of alignment between supply chain capabilities, clinical plans and providing patients with the solution.
In clinical trials, everything is changing every day, which means you need to deal with uncertainty. [There may be] issues finding the right amount of patients in the US; maybe you will find those patients in South America, but maybe it will take a month or two to ship the drug [from one place to another].
You want to be able to re-evaluate this global plan, robust strategy, because it is really complex. Techniques like machine learning may help you leverage the latest information available and help you adapt your global strategy in the best way.
AN: How were some companies able to speed up their drug development processes during the pandemic?
SC: Most pharma companies were struggling in the pandemic with the fact they could not easily supply the sites or, most importantly, get the patients to the sites.
If patients were not able to get to the sites, companies had to pause the clinical trials or find some alternatives, like shipping the drug directly to the patient’s home. This was already an option available before the pandemic, but it was not used because regulation meant it was just not allowed in many different countries. One positive impact of the pandemic was to try and bring in some alternatives to help patients get access to clinical trials.
I believe that the pharmaceutical companies that were more ready and had the right technology available were better able to evaluate and assess the impacts and consequences of the various supply chain challenges met through this pandemic.
Let’s take a simple example. Clinical trials usually take 10 years, and there were some pharmaceutical companies thinking about how can we split this long process into many different small steps and run those in parallel when possible? You need smart planning so you can understand all the consequences and impacts on project timelines. If something goes wrong, we need to adapt to changes. Technology and digitisation are definitely allowing some pharma organisations to quickly do some testing and allow them to find a global strategy to reduce time to market.
AN: Could more digitisation in clinical trials have reduced the disruption the pandemic wrought on clinical research?
SC: This is tricky to answer because it is not easy to know exactly what would have happened [if things were done] in a different way.
Companies that were managing their clinical trials and supply chain within Excel spreadsheets before the pandemic probably did not have the easiest time during the pandemic [in terms of] dealing with a lot of uncertainty and challenges.
Trying to analyse a lot of data within Excel is not the [most] efficient way to invest your time, to find some solutions quickly and get alignment between all the different departments, all with their own spreadsheets. When you’re sharing data in Excel, the trust may not be there.
A really important point for me when speaking about digitisation is about the trust you may have in the data. If you’re bringing data not from Excel, but from a trusted system, you can connect the dots. This means sharing data with the different departments and stakeholders within the pharmaceutical organisation and then you can discuss the data and challenge the data with machine learning. That is really where I believe technology helps companies.
[Technology improves] your ability to react to changes. For instance, the recruitment may have gotten slower in Brazil, but much faster in Asia. [So] maybe you want to adapt your capability to supply a bit more to patients in Asia, but less in South America where the situation is under control for another couple of months.
AN: What learnings from the pandemic will benefit clinical development in the future?
SC: At some point, there will be big benefits coming from this crisis because we can see it is possible to reduce the clinical development timelines. It is possible to split some standard activities into multiple smaller pieces and run them in parallel.
But should you want to do this, you should be able to plan ahead and understand all of the consequences in terms of timelines, projects, and who is responsible for which actions. This will involve not only technology, but adapting the processes and structure.
[Better clinical trials] will be a really important goal for pharmaceutical companies within the next few years. It will come from top management and senior leadership who want to see reduced timelines in the coming decades. You cannot be part of the leadership of a pharma organisation and believe it is still okay to wait ten to 15 years to get drugs commercialised.
As a consequence, I am expecting a lot of organisations to invest massively in technology and digitisation, [particularly] machine learning, advanced analytics and other techniques, to help them to adapt their processes and their structure to connect the dots between different departments. Technology is there to help pharma organisations plan the way to manage risk, time and investments, and allow them to shift from one model to another.
The way clinical trials will be run in the future will be different to the way they were run a couple of years ago.