Choose wisely

30 January 2020



Choosing the right vendor is a hugely important aspect of planning for a clinical trial. There are a number of different factors to consider when working with these contract research organisations. Emma Green speaks to Ken Getz, director of sponsored programmes, research professor at Tufts Center for the Study of Drug Development, about the key strategies to ensure smooth study delivery.


The long-term nature of clinical trials, along with their crucial role in getting drugs to market, means that engaging with the right contract research organisation (CRO) is imperative. As with any important business decision, the selection process cannot be rushed, as doing so could jeopardise the quality of the study, negatively impacting all parties involved.

Ken Getz, director of sponsored programmes, research professor (PHCM) at Tufts Center for the Study of Drug Development (CSDD), has a wealth of experience and knowledge of vendor selection. With a background in science and economics, he can speak to both the research literature and real-world practices. Getz worked as a consultant within a nonprofit organisation before taking on an academic role, and as a result is attuned to the needs and concerns of pharma companies, CROs and patients.

For Getz, when choosing a vendor for a trial, asking a lot of questions up front is key – this includes investigating expertise and competency.

“Does the CRO have a specific skill set or experience with a particular disease, patient population or molecule?” he asks.

The vendor company culture is another key consideration, according to Getz. “What is their culture like? What are they like to work with? How do they operate as a part of the team, for example? There is the whole aspect of background information. What is the history of the company? Are they financially healthy? What is their past record of performance?”

Ensuring adequate ability to meet regulation is also imperative. “Are they 21 CFR-compliant? Do they have all the necessary controls in place to meet regulatory requirements?” Getz asks.

Reassuringly, he feels that most pharma companies are already asking these kinds of questions. “Given the incredible pressure on our industry to comply with regulation, to meet critical and aggressive timelines, and to manage tight budgets, I think that the industry takes the assessment of these relationships extremely seriously,” he says.

80%
Pharma companies are supporting some of their development activities through using AI.
Tufts Center for the Study of Drug Development

“Technology and data could play a much greater role in supporting integration and, ultimately, facilitating more timely and informed decision-making.”

Best practices

Although specifics vary depending on the pharma company and the nature of the trial, there are some universal best practices.

“A high level of responsiveness and transparency, processing information from CROs efficiently and creating kind of a template set of processes that can be followed,” says Getz. “All of that helps immensely.”

This doesn’t rule out an individualised approach. “A lot of the elements are more subjective and intuitive, and those are the ones where each company sort of has its own rules that might become best practices,” says Getz.

However, there is a trade-off to be made between customisation and consistency. “Even in companies that have a set of preferred vendors, we still see a lot of mixing and matching of parties that are brought in that are new to the organisation,” explains Getz. “Each relationship becomes more of a custom approach, and usually results in longer timelines and more inefficiency,” explains Getz.

These practices do not result from a lack of care or consideration. “A lot of individual teams think that their projects are unique and require that level of flexibility,” says Getz. “When we see that kind of behaviour, if you look at the macro level, the variation, the amount of time that it takes and the performance of the companies suggests that they are forfeiting the ability to choose and manage these relationships more efficiently.”

Leveraging technology and data

Of course, any aspect of clinical trials cannot be addressed without a discussion of the role of technology. “I see both data and technology as critically important on many levels,” says Getz. “There is a wealth of information that is gathered in disparate places in organisations, which could be used to more prudently evaluate and select vendors.”

This analysis might seem an onerous task but can really pay off. “Instead of reinventing the wheel each time, we could be using data from a lot of different solutions that were used for past relationships,” explains Getz. “There are a whole host of solutions that can be used to better integrate external service providers and internal organisations. Both technology and data could play a much greater role in supporting integration and, ultimately, facilitating more timely and informed decision-making.”

In light of the high level of enthusiasm inside and outside the industry for advances in technology, it can be hard to understand why these solutions are not more readily implemented. A key reason is the lack of communication between the different individuals involved.

“Many of the solutions are siloed, so it is often hard to get access to that kind of information,” says Getz. “Procurement has its own ways of tracking different things, clinical operations has its clinical trials management system, it has recruitment and retention tracking, and contracting and budgeting, and all kinds of different solutions that often are not really speaking with each other.”

Time is also a factor. “The timelines are so aggressive, the different functions that are all supporting a specific study don’t always have a chance to share this information in a timely and integrated way,” explains Getz. “Each is making decisions based on a limited set of data.”

Fortunately, the resources and tools are available – it is more a matter of changing working practices to make better use of them.

“Companies are collecting a tremendous amount of data, perhaps more than is really necessary, but it is not being unified in any real way,” says Getz. “We see organisations talking about data lakes, and ways of overlaying the software and AI to analyse and evaluate a much higher volume of data, but right now much of the data is just scattered, not accessible, not integrated, so it is hard to see the full picture.”

Companies are becoming increasingly aware of the need for improvement in this area. “There are lots of internal initiatives within companies as well as vendors that are trying to lead solutions,” says Getz. “The jury is still out as to which approach might work best and depending on the company, you are going to see lots of different models.”

Software solutions

It is unclear which of these might be more effective. “Some believe that data analytics will be a decentralised capability, where every person needs to become their own data scientist,” explains Getz. “Others feel that making it more of a centralised activity [is preferable], where you might even have a group of trained data scientists who might be able to expedite that kind of capability.”

There is certainly a wealth of options to choose from. “There are lots of software solutions that are now being used,” says Getz. “Some are off-theshelf that are really powerful, which I see on the desks of very junior-level data scientists. Others are very complex and powerful solutions that are sitting on platforms analysing huge volumes of data, which can be used to select investigators and vendors, improve the identification, selection, recruitment and retention of study volunteers, and monitor patient response to new treatments while a trial is under way.”

Looking outwards can also be helpful. “There are some industries that are further along in their use of really powerful analytic tools, including AI such as natural language processing and machine learning,” says Getz. “Some have years of experience in using those tools and there is a lot that can be learned there.”

“Companies are collecting a tremendous amount of data, perhaps more than is really necessary, but it is not being unified in any real way.”

Starting small when testing different technologies is key, which is now being implemented more readily. “We are already seeing a tremendous amount of piloting going on in the industry,” says Getz. “Over 80% of major pharma companies tell us that they are using AI to support some of their development activities.”

There is also a role for CROs in the integration of more advanced and novel technologies. “CROs, in order to differentiate themselves, will help drive the adoption of these new solutions,” explains Getz. “Their own effectiveness and viability depends on the integration and more thoughtful use of data and analytics to support highly complex activities. I think all the CROs have come to the conclusion that instead of waiting for sponsor companies to leverage the value of these assets, it might make sense for them to help facilitate their implementation.”


CRO size and therapeutic expertise: results from an Industry Standard Research (ISR) survey

Therapeutic expertise has remained among the most important attributes from year to year, across trial phases, regardless of whether there are preferred provider agreements in place. An organisation’s therapeutic expertise (or lack thereof) is often commented upon when respondents explain their reasoning for assigning overall satisfaction scores for CROs they have recently used. In short, a provider’s knowledge of the desired therapeutic areas and its prior experience working in these areas go a long way in determining whether a provider is chosen for a clinical study.

Where does CRO size come into play? Size is undoubtedly a factor in an organisation’s ability to deliver global studies or offer a one-stop-shop experience – but how does provider size affect customers’ perceptions of therapeutic expertise? Over the past decade of researching service provider selection, ISR has often seen outsourcers attributing smaller CROs with superior therapeutic expertise in their areas of speciality compared with large CROs.

In order to gather the opinions of a larger group, Life Sciences Leader asked more than 500 clinical development outsourcers about their levels of agreement with the following statement: ‘Small/niche providers that specialise in only a few therapeutic areas offer a higher level of therapeutic expertise than large CROs’.

About three quarters of respondents agreed with this statement. Around 40% indicate that their agreement is moderate to strong. Unquestionably, there are many other factors that go into the decision of which CRO will shepherd a molecule through critical clinical trials — geographic footprint, service capabilities, project manager quality, patient recruitment abilities and cost, to name a few. However, the perception that small/niche providers have better therapeutic expertise than their larger counterparts is an interesting one. Small organisations can tout their deep therapeutic expertise in specific areas in marketing messaging, and this data shows that audiences are likely to find these claims credible. Large CROs may do well to message around their therapeutic expertise as well — perhaps along the lines of ‘our therapeutic breadth doesn’t come at the expense of depth’.

Source: Life Sciences Leader



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