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Page 48 Tarantino et al. Cancer Drug Resist 2019;2:43-52 I http://dx.doi.org/10.20517/cdr.2018.22

Figure 3. Possibilities of PGx implementation in each R&D phase

[34]
of dose-limiting toxicities , the selected dose for expansion trials (and finally for its approval) was 2mg/kg,
[35]
based on translational models and pharmacokinetic/pharmacodynamics studies . Such evidence promoted
the adoption of new, Bayesian designs, allowing to more rapid dose escalation and the definition of a dose-
toxicity curve to which all patients enrolled in the trial contribute. In the setting of dose-finding, the concept
of biomarker-based dosing algorithms was proposed, based on the assumption that the PGx profile could
help defining the optimal drug dose for each patient. Indeed, not every type of gene alteration is equally
actionable, as it is exemplified by the different sensitivity of HER2-amplified and HER2-mutated cancers
[36]
to anti-HER2 agents ; in this setting, Bayesian phase 1 and 2 study designs have been proposed to adapt
[37]
drug doses to patient’s PGx profile . The rise of more flexible study designs helped in the assessment of the
role of biomarkers, even in the small cohorts of phase 1 studies: in the case of pembrolizumab, for instance,
data regarding PD-L1 expression and activity in 15 patients informed later phases, leading to the cut-off
identification of PD-L1 > 50% in NSCLC in a relatively short time. Generalizing this concept, even the small
ratio of positive PGx findings of Phase 1 studies may be critical in contributing to more effective Phase 2-3
studies and shorter time to developmental decisions, orienting the investments and reducing the rates of
patients less likely to derive a clinical benefit from drugs under development.

Phase 2 trials aim to assess drug efficacy, as well as further evaluate its safety. They enroll a higher number
of patients, usually with a specific type of cancer and treated with fixed drug doses (the RP2D). All of these
[30]
features make this setting the most promising for identifying efficacy biomarkers: O’Donnel and Stadler et al.
report a 70% success ratio in identifying “positive” PGx findings (worthy of additional follow up and
validation) in a cohort of 57 Phase 2 studies which incorporated PGx. PGx biomarkers can be implemented
in different ways into phase 2 trials, depending on the characteristics of the biomarker. The enrichment
design, for instance, screens patients for the presence or absence the PGx biomarker and then only includes
patients who either have or do not have the marker in the clinical trial; this design is clearly beneficial when
there is a strong preliminary evidence (e.g., deriving from phase 1 trial results) to suggest benefit only in
the biomarker-defined subgroup, and/or when the marker prevalence is low (therefore the risk of diluting
the drug effect by treating un unscreened population is high). In the allcomers design, instead, all patients