Contract Research Organization – Design and Development in Oncology CRO Services
The value of design and development often goes unrecognised when providing Oncology CRO Services.
The value of a molecule that goes into drug development depends on the dose regimen, the population to which it’s going to be administered and even the sample size. This can impact the probability of approval or probability of technical success.
The Usefulness of Adaptive Designs in Oncology CRO Services
Typically, a contract research organization starts with a larger number of doses and then you have multiple interim analyses and each interim analysis is based on the data observed in a pre-specified algorithm.
The dose is switched more and more towards the one performing the best, so this adaptive algorithm discontinues some doses that are not performing well and focuses on the ones that are most promising.
It has been demonstrated repeatedly by contract research organizations in simulations, that generally adaptive designs are the most efficient approach with this stage of development because of their flexibility. Usually, multiple doses are not studied in oncology.
The normal practice when providing oncology CRO services is to go into phase one with limited sample size and as a result of that, there is really a limited level of confidence whether the maximum tolerated dose is identified or not. Nevertheless, this level of dosage is the basis of the rest of the drug development.
In Phase 2, what is traditionally done is that only one dose in with a single regimen is taken and it usually looks like a mini Phase 3 trial.
In reality, this is just another checkpoint to determine whether it is worthwhile to go into the larger Phase 3.
Quite often in Phase 3 oncology trial, the drug fails and that is because it really has never been given a fair chance to get through development. The success rate in oncology is really low particularly when it comes to Phase 3.
Phase 2 generally is the stage where drug development can be optimized because selecting a good dose gives better chances for regulatory success. It gives you a better chance for differentiation after approval so it’s really worth investing a little more into this stage of development.
Usually, testing starts with some POC followed by a dose-finding study where a number of doses and then if needed consider a definitive dose-response. It is useful to study multiple regimens or in the case of combination therapy, a whole grid of possible combinations of two drugs.
When studying multiple regimens, these can be combined in a single study using an adaptive design
At this stage, there may be one or two candidate indications or regimens which can be combined in one study where after interim analysis one regimen is selected and then at the second stage of that trial efficacy can be demonstrated with the selected regimen.
Running simulations and combining these can prove to be much more efficient in phase two and three because all that’s really being done is having another checkpoint. All that this requires is an additional interim analysis which saves a lot of in time development, certainly in cost for the contract research organization.
There is also a much better probability of success because the same patient is being used for two objectives.
Adaptive Designs in the Confirmatory Stage
In the therapeutic areas confirmatory stage there are three main types of adaptive designs. They all address some uncertainties when entering into Phase 3 and by a reassessment of the sample size, if there is still uncertainty about the treatment effect, and in oncology, there is always some because the endpoint in Phase 3 is usually overall survival.
Normally there’s not much time to obtain robust data on overall survival prior to getting into Phase 3 so this is one way minimising the risk in drug development in this phase.
An interim analysis will assess whether an initial sample size is large enough to assure the proper relevance. There still may be questions about what is the best dose, so it’s best to go with a couple of them at an interim analysis.
Data from both stages can be used when providing oncology CRO services, however, it needs to be adjusted for multiplicity for type 1 error.
Impact of Adaptive Enrichment
In terms of labelling, the FDA has a draft guideline which implies that the use of predictive enrichment is limited and from this perspective, it may not look appealing in terms of the population size commercially.
However, during the development and particularly with the help of the adaptive enrichment design it is possible to differentiate better so there is an improved chance of obtaining regulatory approval.
Aside from drug approvals, customers should also be considered by the contract research organization in terms of the value of the drug on the market. Adaptive enrichment gives an opportunity for premium pricing based on a differentiated product.
Considering how the Phase 2 and Phase 3 development path may look when it comes to biomarkers,
let’s assume there is one single candidate biomarker who may have scenarios, which when looking at the whole population results in a negative in Phase 2 trials.
One can be very adaptive here because these results are not a part of confirmatory evidence and it is still possible to look into subpopulations particularly if the subpopulations of interest have been specified.
If there is a negative result in the whole population it is still possible to look at biomarker in a subpopulation. If that is also negative then it indicates that the development of the drug may as well be stopped.