Pharmacokinetics of intranasal drugs, still a missed opportunity?

The intranasal (IN) route of administration is important for topical drugs and drugs intended to act systemically. More recently, direct nose-to-brain input was considered to bypass the blood-brain barrier.Processes related to IN absorption and nose-to-brain distribution are complex and depend, sometimes in contrasting ways, on chemico-physical and structural parameters of the compounds, and on formulation options.Due to the intricacies of these processes and despite the large number of articles published on many different IN compounds, it appears that absorption after IN dosing is not yet fully understood. In particular, at variance of the understanding and modelling approaches that are available for predicting the pharmacokinetics (PK) following oral administration of xenobiotics, it appears that there is not a similar understanding of the chemico-physical and structural determinants influencing drug absorption and disposition of compounds after IN administration, which represents a missed opportunity for this research field. This is even more true regarding the understanding of the direct nose-to-brain input. Due to this, IN administrations may represent an interesting and open research field for scientists aiming to develop PK property predictions tools, mechanistic PK models describing rate and extent of IN absorption, and translational tools to anticipate the clinical PK following IN dosing based on in vitro and in vivo non clinical experiments.This review intends to provide: i) some basic knowledge related to the physiology of PK after IN dosing, ii) a non-exhaustive list of preclinical and clinical examples related to compounds explored for the potential nose-to-blood and nose-to-brain passage, and iii) the identification of some areas requiring improvements, the understanding of which may facilitate the development of IN drug candidates.

Biomarker- versus drug-driven tumor growth inhibition models: an equivalence analysis.

The mathematical modeling of tumor xenograft experiments following the dosing of antitumor drugs has received much attention in the last decade. Biomarker data can further provide useful insights on the pathological processes and be used for translational purposes in the early clinical development. Therefore, it is of particular interest the development of integrated pharmacokinetic-pharmacodynamic (PK-PD) models encompassing drug, biomarker and tumor-size data. This paper investigates the reciprocal consistency of three types of models: drug-to-tumor, such as established drug-driven tumor growth inhibition (TGI) models, drug-to-biomarker, e.g. indirect response models, and biomarker-to-tumor, e.g. the more recent biomarker-driven TGI models. In particular, this paper derives a mathematical relationship that guarantees the steady-state equivalence of the cascade of drug-to-biomarker and biomarker-to-tumor models with a drug-to-tumor TGI model. Using the Simeoni TGI model as a reference, conditions for steady-state equivalence are worked out and used to derive a new biomarker-driven model. Simulated and real data are used to show that in realistic cases the steady-state equivalence extends also to transient responses. The possibility of predicting the drug-to-tumor potency of a new candidate drug based only on biomarker response is discussed.

Characterizing Effects of Antidiabetic Drugs on Heart Rate, Systolic and Diastolic Blood Pressure.

A model-based meta-analysis was performed with reported data from obese subjects and patients with type 2 diabetes (T2DM) to characterize the effects of dipeptidyl peptidase 4 (DPP4) inhibitors, gastric inhibitory polypeptides (GIPs), glucagon-like peptide-1 (GLP1), and dual GIP/GLP1 agonists, or a combination of these antidiabetic drugs (ADs) on heart rate (HR), diastolic blood pressure (DBP), and systolic blood pressure (SBP). A systematic literature search and review after the Cochrane method identified sources for investigational and approved ADs resulted in a comprehensive database with data from 178 clinical studies in obese subjects and patients with T2DM. Results indicated that there were AD class-dependent effects on HR and SBP, whereas no clear AD-related effects on DBP were found. All AD classes, except for DPP4 inhibitors, increased HR. The largest increase of 12 bpm was seen with GLP1 receptor agonists. All AD classes appeared to decrease SBP. DPP4 inhibitors were associated with a marginal decrease of ~ 1 mmHg, whereas GLP1 and GIP/GLP1 dual agonists exhibited the largest decrease of ~ 3 mmHg in SBP. AD-related effects were similar in obese subjects and patients with T2DM. In conclusion, there are clinically relevant AD-related effects on both HR and SBP, but not on DBP. DPP4 inhibitors are associated with the smallest (if at all) effects on HR and SBP, whereas GLP1 inhibitors exhibited the largest effects on these two cardiovascular end points. Additional studies are warranted to further investigate how AD-related SBP decreases combined with HR increases affect long-term cardiovascular mortality.