Purpose: Ivermectin (IVM) is a lipophilic BCS-II compound (molecular weight=875 g/mole, LogP=3.22, intrinsic solubility=700 ug/L). IVM is used as antiparasitic drug in both humans and animals. IVM is known to have a half-life of 12-56 hours in humans. Strongyloidiasis is a chronic parasitic infection of humans caused by Strongyloides stercoralis, with an estimated 30-100 million people infected worldwide. Infection may be severe and even life-threatening in cases of immunodeficiency. Patients with disseminated strongyloidiasis are usually bedridden hospitalized patients that show symptoms such as paralytic ileus and reduced plasma albumin and cholesterol. Oral IVM is the only FDA-approved treatment but may not be effective in patients with disseminated disease. Veterinary subcutaneous formulations have been used in severe infections. We hypothesized that IVM PK in patients with disseminated strongyloidiasis can be predicted using PBPK model originally built and refined in healthy human and animal species. This hypothesis was tested and shown to be valid. Methods:A systematic method was used to build and refine different parts of the PBPK model. The process involved construction of models, parameterization of these models, evaluation of the effect of uncertainty in model parameters on model prediction via local and global sensitivity analyses and finally, refinement of model predictions. Two disposition models that differ in the rate limiting step in drug distribution were constructed and include perfusion-limited and permeability-limited distribution models. The ability of each model to predict IVM disposition was evaluated using plasma PK data in rat after intra-arterial dosing and in dog after intravenous bolus dosing. Then the disposition model was scaled to humans and an oral input model was constructed as a modification on the well-known ACAT model. The oral input model was coupled with the disposition model and used to predict IVM plasma concentration-time profile in healthy fasted human subject after oral dosing. Two subcutaneous (SQ) input models were constructed and used to evaluate the effect of IVM precipitation at the injection site. Plasma PK data in dog after SQ dosing was used to refine the constructed SQ input models. The refined disposition, oral input and SQ input physiologically-based models were used to predict IVM PK in patients with disseminated strongyloidiasis after a complex dosing regimen. The physiological parameters of the model were modified to account for the effect of the disease-induced pathophysiological changes on the body physiology and hence on the drug PK. Plasma PK data from hospitalized subjects with disseminated strongylidiasis was used in this part. Results and conclusions:The disposition model with assumption of permeability-limited distribution was more capable of describing IVM disposition in rat after intra-arterial dosing compared to when perfusion-limited distribution was assumed. The model predicted that hepatic clearance is the most impactful parameter on model-predicted plasma concentration of the drug. Also, IVM was shown to have low hepatic extraction ratio along with high binding in plasma and large volume of distribution, which collectively may explain the long half-life in the plasma of 63 hours in rat after intra-arterial dosing. The oral input model predicted that the oral input is limited by drug dissolution in the GI lumen and that a very small fraction of oral tablet dose (0.03) is available in the systemic circulation in healthy fasted human subjects. Both of the studied SQ input models predicted that majority of IVM absorption after SQ dosing is via the lymphatic route and that drug precipitation at the injection site can further slowdown the drug absorption after SQ administration. The PBPK model was able achieve the main goal of this research which is to predict IVM pharmacokinetics in patients with disseminated strongyloidiasis after a complex dosing regimen of multiple oral and SQ dosing. This was achieved by modifying the most impactful physiological parameters of the model affected by the disease state and that are related to drug binding in the plasma (fraction unbound), the GI motility (gastric emptying rate) and the lymphatic flow rate. Based on our analysis, we recommend measurement of plasma IVM concentrations early after initiation of therapy to exclude treatment failure due to reduced oral and/or SQ absorption. Also, we recommend measurement of plasma lipoprotein levels and their composition in these patients to differentiate between low total plasma concentrations due to low binding plasma as opposed to low drug input. Finally, interventional procedures that enhance lymphatic flow rate to site of SQ injection are recommended to enhance SQ absorption.

The majority of drugs available on the market are intended to be administered through the oral route. To achieve the desired therapeutic effect, an orally administered drug must first reach the systemic circulation and then its site of action. The fraction of the administered drug that reaches the systemic circulation is known as oral bioavailability and it is the product of the absorption and first-pass metabolism processes occurring in both the GI tract and the liver. The factors controlling bioavailability are manifold –both drug and physiologically related - and their complex interplay is key to defining a drug’s oral bioavailability. In drug discovery and development it is therefore pivotal to anticipate and understand the bioavailability of a drug candidate; a far from simple task, considering the multifactorial nature of the process. For that reason, the overall aim of this thesis was to provide different modelling and simulation (M&S) strategies that can be used for the prediction of oral bioavailability that can be of use in drug discovery and development. The first part of this thesis was focused on the evaluation of the use of bioavailability data obtained from pre-clinical species as a predictor of the human value, in a more traditional approach. In particular, the aim was to evaluate models that can quantitatively and qualitatively provide a relationship between animal and human bioavailability, by analysing trends in a large bioavailability dataset. This section demonstrated that although pre-clinical species cannot quantitatively predict bioavailability, the data obtained from them can be used for qualitative prediction of the human value. Nevertheless, such a modelling approach does not provide a mechanistic rationale of the factors affecting the bioavailability differences. Consequently, the second part of this thesis was focused on such mechanistic predictions. Particularly, we investigated the impact that drug release patterns can have on drug absorption and intestinal first pass metabolism, taking into account the physiological differences observed across the length of the human gastrointestinal (GI) tract. These release patterns are suspected to lead to bioavailability differences due to changes in the first-pass metabolism, especially for CYP3A substrates. Therefore we investigated this phenomenon applying a physiologically-based pharmacokinetic (PBPK) M&S approach: firstly, from the discovery point of view, using PBPK models in a prospective fashion to investigating the drug-related factors that might lead to such differences and secondly, from the development point of view, to predict the mechanistic differences in absorption and metabolism of oxybutynin, a drug known for its higher bioavailability when formulated as a modified release (MR) product. The latter was done by developing and applying a novel simplified PBPK model to predict such differences. The results of this work showed that the intestinal metabolism can be significantly reduced when having MR formulations of CYP3A substrates which, in some cases, can lead to higher relative bioavailability. Additionally, this thesis provided novel methods and models that have the potential to improve bioavailability predictions when using PBPK models, in particular for drugs formulated as MR.

Tuberculosis, the leading cause of death by a single infection disease caused by bacteria, requires long treatments and the bacteria are prone to develop drug resistance. Therefore, new efficient treatment regiments needs developing, which requires new tools for drug development. A major reason for discontinuance of a drug under development is undesired pharmacokinetic properties. Therefore, it is important to have early information of this, preferably the first time the drug is tested in animals. The first in vivo pharmacokinetic experiment is often done in mice and the only information present at this stage are often in vitro values and physicochemical properties. Physiological-based pharmacokinetic modelling can be used to extrapolate from in vitro to in vivo values. From this, the first in vivo pharmacokinetic experiment can be designed, often with the goal of reducing the amount of mice. This goal is one of the three R.s and it is called Reduction. To explore the Reduction of an experiment population pharmacokinetic modelling can be utilized via exploration of the imprecision, bias and probability of an informative experiment to evaluate if a design meets the goal of Reduction. In this report a recommendation of the first in vivo pharmacokinetic experiment is presented. This is based on in vitro values and physicochemical properties that are common in anti-tuberculosis drugs. If the probability of an informative experiment is critical, a terminal sampling of 40 mice is recommended. If imprecision and bias are necessary, zipper sampling of 10 mice is recommended.