Clinical Application of Pharmacokinetics in Psychiatry
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The information gathered in Phase 2 serves the dual purpose of studying safety and efficacy while providing proof to the sponsor that the drug is worthy of further development. The pivotal Phase 2 study for continuation of Phase 2 and/or starting Phase 3 is often called ‘Proof of Concept (POC).’ The value of PK measurements in Phase 2 adds another layer of understanding how the body processes the drug; these studies determine differences in PK data between categories of patients, namely those with the targeted disease and normal healthy volunteers.
However, it is possible that an ADHMET approach may be used after Phase 2a or in late clinical development (examples above) provided that adequate PK sampling had been conducted in earlier phases (Robinson D, Woerner MG, Alvir JM, Bilder R, Goldman R, Geisler S, Koreen A, (1999)). It should be noted that this metric is cumulative and is not representative of adherence with the exact time of dosing; however, while the exact time of dosing becomes more critical as the dosing interval exceeds the terminal half-life of the compound, oral therapies are commonly developed for once-daily dosing accompanied by appreciable accumulation to steady-state, where minor deviations in the dosing time may not drastically affect the average profile. Another limitation of the work is its partial dependence on observed PK variability for a given compound, which could be a potential limiting factor for detecting relationships from a sample size perspective (Liu X, Chen Y, Faries DE (2011)). Given that the aggregate adherence metric is a convolution of expected (normal) variability and adherence factors, it is not believed to be appropriate for indicating individual adherence levels. However, neither the magnitude of expected variability in the population, nor the lack of sensitivity at the individual level, are expected to effect the utility of the aggregate adherence metric for group comparisons—only the power to which a difference may be detected across those groups (Marder SR (2003)).
As a general principle, drugs that are metabolized more quickly and have a lower bioavailability carry a higher potential risk of interactions. Predicting pharmacodynamic interactions often requires a deeper understanding of the mechanisms of action; but here too a certain system can be recognized, just as for pharmacokinetic interactions. Electronic prescribing systems that can alert the user early on to possible interactions and can assist with drug selection and dosage are helpful.
Marder SR (2003) Overview of partial compliance. J Clin Psychiatry 64(suppl 16):3–9
Gilbert PL, Harris MJ, McAdams LA, Jeste DV (1995) Neuroleptic withdrawal in schizophrenic patients. A review of the literature. Arch Gen Psychiatry 52(3):173–188
Liu X, Chen Y, Faries DE (2011) Adherence and persistence with branded antidepressants and generic SSRIs among managed care patients with major depressive disorder. Clinicoecon Outcomes Res 3:63–72.
Robinson D, Woerner MG, Alvir JM, Bilder R, Goldman R, Geisler S, Koreen A, Sheitman B, Chakos M, Mayerhoff D, Lieberman JA (1999) Predictors of relapse following response from a first episode of schizophrenia or schizoaffective disorder. Arch Gen Psychiatry 56(3):241–247
Subotnik KL, Nuechterlein KH, Ventura J, Gitlin MJ, Marder S, Mintz J, Hellemann GS, Thornton LA, Singh IR (2011) Risperidone nonadherence and return of positive symptoms in the early course of schizophrenia. Am J Psychiatry 168(3):286–292.