Impact of Changes in Free Concentrations and Drug-Protein Binding on Drug Dosing Regimens in Special Populations and Disease States

Abstract

Over the last few decades, scientists and clinicians have often focused their attention on the unbound fraction of drugs as an indicator of efficacy and the eventual outcome of drug treatments for specific illnesses. Typically, the total drug concentration (bound and unbound) in plasma is used in clinical trials to assess a compound's efficacy. However, the free concentration of a drug tends to be more closely related to its activity and interaction with the body. Thus far, measuring the unbound concentration has been a challenge. Several mechanistic models have attempted to solve this problem by estimating the free drug fraction from available data such as total drug and binding protein concentrations. The aims of this review are first, to give an overview of the methods that have been used to date to calculate the unbound drug fraction. Second, to assess the pharmacokinetic parameters affected by changes in drug protein binding in special populations such as pediatrics, the elderly, pregnancy, and obesity. Third, to review alterations in drug protein binding in some selected disease states and how these changes impact the clinical outcomes for the patients; the disease states include critical illnesses, transplantation, renal failure, chronic kidney disease, and epilepsy. And finally, to discuss how various disease states shift the ratio of unbound to total drug and the consequences of such shifts on dosing adjustments and reaching the therapeutic target.

Keywords: Disease state(s); Dose-response; Drug distribution; Drug transport; Protein binding; Special populations.

Figure 1.

The plasma protein binding (PPB) of some of the top 100 most prescribed drugs. Many of the top 100 most prescribed drugs have greater than 98% PPB, as shown by approximately 2 log units difference in unbound and total plasma concentrations (indicated by the diamonds).2 Reproduced with permission from [2].

Figure 2.

Recommendation for evaluation of protein binding in the clinical development. The role of PPB on efficacy models needs to be rigorously evaluated and established throughout the preclinical and clinical development stages as suggested and outlined by this general scheme. PPB: plasma protein binding; NTI: narrow therapeutic index.3 Reproduced with permission from [3].

Fig. 3

Main factors responsible for alterations in drug-albumin binding. There are many patient presentations that will affect protein binding. The likelihood of altered protein binding is more common in some patient populations such as burn injury patients, cancer, diabetes mellitus, liver disease, and renal disease. SIRS: systemic inflammatory response syndrome.4 Reproduced with permission from [4].

Fig. 4.

Observed cefazolin concentrations in morbidly obese patients. The area under the time–unbound concentration curve (fAUC0–4h) for subcutaneous ISF was significantly lower in morbidly obese patients (n = 7) in comparison with non-obese patients (n = 7), P < 0.05. In contrast, the fAUC0–4h for unbound plasma cefazolin concentrations did not differ significantly between the patient populations (P > 0.05). The observed unbound cefazolin ISF penetration ratio, expressed as fAUCtissue/fAUCplasma, was 0.70 (range 0.68–0.83) in morbidly obese patients as opposed to 1.02 (range 0.85–1.41) in non-obese patients (P < 0.05). Morbidly obese: black symbols and line. Non-obese: grey symbols and line. ISF: interstitial space fluid.37 Reproduced with permission from [37].

Fig. 5

Variability in in vitro plasma protein binding of tacrolimus in individual liver transplant recipients. In liver transplant recipients the unbound fraction of radiolabeled tacrolimus in plasma was found to be 0.47 ± 0.18% and there was a 15-fold variation (range 0.07–0.89%) in the fraction unbound (%) of tacrolimus in these patients. A significantly higher fraction unbound was observed in male recipients (n = 23) compared with female recipients (n = 17) (0.5 ± 0.1% vs 0.4 ± 0.1%; P = 0.003, Student’s t-test). Dashed line indicates average fraction unbound in total cohort (0.47 ± 0.18%).48 Reproduced with permission from [48].

Fig. 6

Valproic acid (VPA) unbound concentrations versus total concentrations (small graph). Total VPA concentrations were measured in 121 patients, with a median concentration of 52 mg/L (11–139 mg/L). Six of these 121 patients (5.0%) had elevated total VPA concentrations (i.e., 100 mg/L). This is in contrast with the 37% of patients who had elevated unbound VPA concentrations. The median-free fraction was 19.3% (8.4%–81.7%). VPA: valproic acid.60 Reproduced with permission from [60].