Conducting a successful oncology development program under Project Optimus requires increased emphasis on determining the optimal dose for the compound under study. Rather than a singular focus on the maximum tolerated dose (MTD), oncology drug development under Project Optimus requires one to develop an approach based on all available data. This includes safety, response rate, biomarker responses, and pharmacokinetics.

The increased emphasis on determining the optimal dose has led to several changes in how clinical trials for oncology drugs are conducted. Here, we will describe several case studies that will demonstrate how innovative study designs and clinical pharmacology may be used to speed development of oncology assets under Project Optimus.

Dose escalation in oncology drug development

There are three main goals of dose escalation in oncology drug development: to determine 1) the dose range where efficacy might be safely explored; 2) the maximum tolerated dose, if obtainable; and 3) the minimum active dose.

A wide range of designs for dose escalation can be used, the majority of which fall into one of two categories: algorithm-based and model-based designs. These design categories differ in several ways, as illustrated in Figure 1.

Figure 1: Comparison of algorithm and model-based methods

Algorithm-based methods are conventional design methods that use prespecified rules to determine dose escalation and de-escalation. The classic 3+3 design, for example, is still used fairly frequently, despite its documented shortcomings. For example, the “3+3” design may recommend a Phase 2 dose that is too high, it is unable to include intermediate doses, and there are difficulties with handling cohort numbers that are not multiples of three.

Model-based methods, on the other hand, have significant advantages over algorithm-based methods, since prior information may be used. These adaptive design methods may provide information on intermediate doses not studied. However, because the “3+3” design has been in use for so long, there is considerable inertia among trialists to adopt better designs.

Newer algorithmic designs, such as mTPI-2, BOIN, i3+3, and model-based designs, such as BLRM, should be carefully considered.

In the age of targeted immune-oncology agents, the concept of the Maximum Tolerated Dose (MTD) is assuming less importance, as the optimally efficacious dose of these products is usually lower than the MTD. There are newer study designs that consider not only toxicity, but also efficacy. These designs, such as J3+3, PRINTE, TEPE, EFFTOX and UBOIN, are more suited for modern targeted agents.

Pharmacokinetics and pharmacodynamics in oncology drug development: Case studies

There are many reasons to closely monitor pharmacokinetics (PK) during the initial dose escalation phase, including confirmation of exposure predictions, sufficient bioavailability (for oral or subcutaneous drugs), and the potential need for changes in the infusion rate, sampling scheme, or dosing regimen.

To illustrate this: in one case we encountered, the observed exposure was considerably different than what was predicted, and so considerable re-work of doses and dosing regimens had to be performed. The good news is that this was done early, thus minimizing the number of patients exposed to sub-optimal doses.

In another example, poor oral bioavailability was observed early in a dose escalation trial, thus allowing the trial to close early, again minimizing the number of patients treated with a sub-optimal dosing regimen. Building PK models of your drug early allows quick evaluation of the impact of different regimens and infusion times.

Dosing of oncology agents based on some measure of body size has a long history in oncology. Most immune-oncology agents are dosed based on body weight, as clearance of monoclonal antibodies (mAbs) is proportional to weight. Therefore, weight-based dosing is often used in the initial Phase 1 trial. In later studies, weight-based dosing may result in increased costs, as patient kits will have to contain extra vials of the drug to account for the wide range of patient weights that may be encountered. This can result in considerable waste if these extra vials are not used. Post-approval, weight-based dosing can also result in waste, as more than one vial of the drug may have to be used for larger patients, with the remaining portion in the second vial being discarded. To transition from weight-based to fixed dosing, one should perform simulations of weight-based and fixed doses and choose the fixed dose that most closely matches the weight-based exposure (AUC or Cmax).

The role and advantages of measuring pharmacodynamic biomarkers in oncology is sometimes not clear. There are no established surrogate endpoints in oncology, so what do these markers add to your program? The answer is evidence of target engagement. A biomarker closely linked to the mechanism of action of the drug, which changes in response to various doses of the compound, gives added “reason to believe” in the new drug’s mechanism of action.

Exposure-response analyses also help evaluate the relationship between exposure and safety. Evidence of maximum target engagement, coupled with safety and efficacy data, adds credence to the overall data set. (For two case studies illustrating the usefulness of exposure-response data in helping to interpret the overall safety and efficacy data, watch the webinar linked below). One case we encountered showed how exposure-response data for both a safety endpoint and a target engagement endpoint helped with the interpretation of efficacy data, which was promising, but difficult to interpret. The use of biomarkers in an exposure-response context allowed the selection of doses for Phase 2. Another case study showed that, based on a clear exposure-response relationship with a safety endpoint, it would be advantageous to study additional patients at lower doses in order to find a lower dose with the same level of efficacy, but a lower level of toxicity.

Final takeaways

The goal of any study under Project Optimus is to determine the optimal dose, not necessarily the MTD, which is of lesser importance. Newer study design options for immune-oncology products developed under Project Optimus should be considered. These designs have significant advantages over the classical “3+3” design. The pharmacokinetics of your compound should be quantified as early as possible in development in order to 1) confirm exposure, 2) confirm sufficient bioavailability (if administered orally), and 3) investigate whether fixed-dosing (rather than weight-based dosing) may be used. Performing exposure-response analyses using reliable biomarkers can aid in decision-making on doses, by showing target engagement. Exposure-response analyses using safety endpoints can also be extremely helpful in determining doses to take further into development.

Interested in learning more? Our recent webinar, “Oncology Drug Development Under Project Optimus: Case Studies” gives a full breakdown of the case studies mentioned here, and more. Watch on demand:

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