The The Future of RTSM: Insights and Forecasting with RTSM-Expert, Ian Davison:

By all expert accounts, 2022 is the year that we can begin seeing the societal shift from late-stage pandemic to early-stage endemic as the world learns to live with the short- and long-term effects of COVID-19. Clinical trial operations, specifically as they relate to randomization and trial supply, have undergone one of the biggest transformations during the pandemic. With the industry adopting direct-to-patient trial supply and remote monitoring on a larger scale, it begs the question: what pandemic-era changes are here for the long-haul and which are likely to phase out? 

We sat down with Medrio’s internal RTSM-expert, Ian Davison, to explore the impact of the pandemic on trial operations and what the future of RTSM technology looks like. 

Insights and Forecasting with RTSM-Expert, Ian Davison​

Mod: Ian, you’ve spent your 25+ year career in the clinical trial technology space, spending time at both a large CRO and niche IRT services, managing clinical operations and supply management.

In that time, you’ve no doubt seen the way the industry conducts trial operations change drastically with the introduction of new technologies. Speaking just to this year alone, what have been some of the biggest advancements you’ve seen in trial supply management?

Ian: Most of the major changes we’ve seen recently are due largely to the pandemic, which accelerated the rise of direct-to-patient supply, hybrid trial designs, and more. However, it’s too early to know the long-term impact of these changes.

At the beginning of the pandemic, there was a general attempt to just throw our hands in the air! Much of the industry asked how we can cope with the fact that patients are no longer coming to the sites but clinical trials still need to run. Many planned trials were canceled, but for ongoing trials the solution was switching from ship-to-site operations to direct-to-patient trial supply. That’s been one of, if not the key change made in the last couple of years.

It’s not been easy.  Direct-to-patient supply methods face fractured regulations across different parts of the world. We’re seeing many solutions proposed, but regulations may apply in one country, and not another. Even in the U.S., some regulations apply to one state and not another.

How do you see the direct-to-patient trend carrying into the future of clinical trials?

Opinion is definitely divided.

One set are thinking: thank God the impact of the pandemic is behind us and we can go back to doing things the sensible way we used to like—

  • Shipping directly to sites.
  • Conducting risk temperature monitoring.
  • Trusting that there is a trained pharmacist at the end of the supply chain who knows how to deal with our shipment, knows what to do with the temperature log, understands GMP, etc.

The other set are thinking: wow, this is going to change clinical trials forever! Everything is going to switch to direct-to-patient trial supply and we won’t have to rely on sending patients back to a hospital or clinical setting!

Mod: That’s quite a dichotomy. How do you see that panning out for the industry in the coming years?

Ian: The reality is that there is a mixed response in the industry.   and we don’t know which side will prevail. But in talking to clinical trial supply groups, particularly as I’ve begun attending industry events again such as SCOPE and OCT UK/Ireland, I’m finding a common trend.

Clinical trial supply groups say that they’re seeing less demand for direct-to-patient trial supply recently. These are the individuals who have their ‘boots on the ground’ when it comes to trial logistics. It may turn out that this trend is unfounded, but evidence seems clear that once COVID-19 is “behind us”, we may see an increase of patients going back to seeing investigators at the site and an overall decrease in demand for direct-to-patient.  Of course part of this may be the delayed start of trials where the subjects have to visit the clinics.  Monthly telephone visits with Direct to Patient may work for a dermatitis trial but if you need surgery or medical imaging, then you’re visiting the hospital

Mod: If we see the industry shift away from direct-to-patient models, how should companies plan to pivot so it doesn’t look like the industry is regressing away from technological progress? I would imagine many companies still want to incentivize direct-to-patient operations wherever it makes sense.

Ian: Let me be clear — direct-to-patient isn’t going to disappear But I think there’s too much evangelism about how it’s going to ‘take over’ the industry.

In reality, a lot of healthcare is still face-to-face healthcare and it will remain that way. While telemedicine is important and direct-to-patient is important, a lot of patients still prefer going to a clinic and having direct contact with their nurse or doctor.

I think there will remain a demand for direct-to-patient and we should certainly be considering our role in that as a technology vendor. We need to ask how we can integrate direct-to-patient (DTP) workflows as well as the traditional ship-to-site operations. Since there isn’t evidence that DTP is going to flourish and direct-to-site is going to cease, it’s fair to reason that there’s always going to be a mix.

So I guess the question is: What will the mix be?

Mod: How can technology vendors prepare to support direct-to-patient and ship-to-site (STS) operations concurrently?

Ian: The key is flexibility. What we’re seeing fairly regularly now is optional site visits in protocols. Whereas traditionally, a subject may be required to come onsite for visits 1 – 5; now, they may be offered optional in-person or televisit options unless an in-person protocol is necessary.

Supporting the mix of DTP and STS means that companies need a way of pivoting so that whatever choice the subject makes, we have a way to get supply to that subject.

Mod: Being able to offer subjects options and catering to their needs sounds very progressive, but is it easier said than done?

Yes, offering a mix of on-site visits, direct-to-patient shipments, and telemedicine IS easier said than done. There are many privacy issues to consider when going this route. Trial staff outside the site can’t know who the patient is or their address so there needs to be a strict wall between the company delivering to the subject directly and the company running the trial to protect patient privacy. Luckily, there are a whole host of mechanisms for doing that type of delivery.

Ultimately, there is no black and white answer. There will always be a requirement for ship-to-site, as well as a growing case for direct-to-patient, so the best thing companies can do is determine what the best fit is for each individual protocol.

Mod: We’re seeing greater evidence that unifying your trial solutions can help create better efficiencies for your trial operations. How should CROs and sponsors approach sourcing their RTSM and EDC solutions?

Ian: RTSM + EDC integrations are pretty much expected these days. But now the industry expects those integrations to be tight and efficient.

It’s 2022—sites don’t want to be juggling and filling data into two, three, or even four disparate systems. Yet, that’s still happening in many cases. Instead of maintaining an inventory record for their pharmacy in one place and then maintaining sponsor records somewhere else to meet SOPs, sites need a single source of truth for trial management.

Instead of wasting time manually checking data across systems, having a native EDC + RTSM integration automatically ensures information is being recorded across systems and is available on-demand to sponsors, sites, and investigators as needed.

It will always be something that actively needs managing. But our customers will always expect a tight integration.

Mod: Do you think Just-In-Time (JIT) is the way that we should be pushing the industry or is there another method that strikes a better balance between outage and surplus?

Ian: Every trial needs to be examined at the start.

JIT has tremendous value in industries such as manufacturing where you simply don’t want to maintain a costly inventory onsite. You don’t want to spend money keeping things on shelves or paying for inventory storage space. If you’re manufacturing cars, for instance, you want the components arriving at one end of the factory as they’re being assembled. And that’s the most efficient way to do it. That does, however, mean you have a pretty constant logistics process and you have a lot of small shipments. When we’re talking about $100,000 of car parts, shipping costs aren’t a big deal.

But if you’re talking about $25 worth of medication with a $200 logistics cost, then you do NOT want just-in-time because you are going to hugely inflate your costs.

Mod: If JIT doesn’t make sense, what other options may be optimal?

Ian: You need to think about the rationale for JIT. If you’re a smaller trial, you’ve got a tiny amount of product and you want to make it stretch – then you can’t afford to have excess product sitting on shelves at hospitals. You need to tailor your supply chain to be more demand-driven and not necessarily JIT, but lean. In this situation, restocking is driven by what the site requires rather than driven by any sort of shelf stocking methodology.

But at the other end of the scale, there are times when the product is small and can be stored easily at room temperature. The vendor might already have a warehouse full. In this case, there might be no issues with deploying traditional reorder point methods, saving money at the expense of inventory by having efficient logistics.

Mod: How can companies decide which method is best for their operations?

Ian: Simple – sit down in the beginning of your planning stage and ask yourself “What is best for this product? What is best for this particular trial? Are our priorities cost-driven or efficiency-driven?”

The good thing about Medrio RTSM is that it runs along that flexible scale. We help our customers evaluate which method or hybrid methods makes sense for their trial.   We can set up reorder point algorithms – similar to how grocery stores keep their shelves stocked – along side a demand driven component so we can optimize efficiency AND inventory cost savings.

Mod: Machine Learning gets tossed around a lot when it comes to RTSM, but it seems like we’re still in the early stages of those conversations. What do you see as the next evolution of RTSM being supported by ML and AI? And are we still far out from achieving it?

Truthfully, we are still a little way from achieving it. But it’s an exciting area going forward!

The thing about machine learning is that you need a big corpus of data to train the machine. And feedback from us so the machine learns what worked.  ML for a company like McDonald’s that wants to determine how many potatoes should be delivered on a daily or weekly basis is going to have millions of data points spanning tens of years. They can feed their AI-engine with a substantial amount of data to be able to make an informed decision.

Comparatively, the problem with clinical trials is that they’re small. Even a big clinical trial is considered ‘small’ by AI standards. Trials are also traditionally short so they may not be creating enough information to be useful for ML or an AI. We need to compile metadata from a large corpus of trials to train the machines. Definitely worthwhile, and definitely  the future.

Mod: Is there anything companies can be doing now to prepare for ML and AI becoming a bigger part of clinical trials?

Ian: Yes, start thinking about the data you’re collecting now. Having the data is key. For a machine to learn, it needs to have input.

AI could also be powerful for generating simulated trials. Building simulated trial environments and testing scenarios like varying the amount of product, adjusting subject pools, introducing storage or damage variables, can be powerful in generating data to predict subject and supply chain behavior.

Mod: Are we still seeing hesitation to adopt RTSM in 2022?

Ian: It’s not a hesitation to adopt, so much as it is: what stage in the process are companies bringing the vendor into their supply conversations?

Mod: Is there an optimal time to bring RTSM vendors into the conversation?

Ian: Yes. Early. Decisions made on packaging and labeling, and the mechanism to allocate IP to subjects have significant effects on the scope of automation and efficiencies that RTSM can provide.  So it’s not just timing for the RTSM, it’s the consultancy around the RTSM and supply chain operations. Vendors are expected to know how best to use the technology and how to use an RTSM to design a supply management strategy that will deliver the most value to your study.

When companies decide how their trial and its supply chain are going to run before considering the RTSM workflow and capabilities, they are removing the ability to be agile and automate their processes. Unlike other clinical trial technologies, introducing RTSM workflows into your study design early – as much as 10 months to 1 year prior to go-live – is optimal. This not only gives CROs and sponsors the ability to ask questions sooner, but the vendor can streamline the setup process and identify efficiencies that carry throughout the trial.

On the other hand, if a bad operational decision is made early on in the planning process, it may not be feasible to fix it after the RTSM solution is brought on. For example – choosing packaging or shipment mechanisms before onboarding an RTSM vendor can have major ramifications.  I’ve seen phenomenal wastage in clinical trials, and even trials put on hold because inflexibility was ‘designed in’ and the supply chain was too active in supplying the returns and destruction process.

Mod: What is the biggest takeaway that sponsors and CROs should retain from this conversation?

Ian: Regardless of which methodology your supply chain supports or the size or type of your trial, the most important decision that companies need to make is which RTSM solution is going to allow you the flexibility to support your unique trial’s needs. If I could leave you with one takeaway, it is to start your randomization and trial supply conversations early to give your trials the best chance of operational success

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