Mechanistic framework predicts drug-class specific utility of antiretrovirals for HIV prophylaxis.

Currently, there is no effective vaccine to halt HIV transmission. However, pre-exposure prophylaxis (PrEP) with the drug combination Truvada can substantially decrease HIV transmission in individuals at risk. Despite its benefits, Truvada-based PrEP is expensive and needs to be taken once-daily, which often leads to inadequate adherence and incomplete protection. These deficits may be overcome by next-generation PrEP regimen, including currently investigated long-acting formulations, or patent-expired drugs. However, poor translatability of animal- and ex vivo/in vitro experiments, and the necessity to conduct long-term (several years) human trials involving considerable sample sizes (N>1000 individuals) are major obstacles to rationalize drug-candidate selection. We developed a prophylaxis modelling tool that mechanistically considers the mode-of-action of all available drugs. We used the tool to screen antivirals for their prophylactic utility and identify lower bound effective concentrations that can guide dose selection in PrEP trials. While in vitro measurable drug potency usually guides PrEP trial design, we found that it may over-predict PrEP potency for all drug classes except reverse transcriptase inhibitors. While most drugs displayed graded concentration-prophylaxis profiles, protease inhibitors tended to switch between none- and complete protection. While several treatment-approved drugs could be ruled out as PrEP candidates based on lack-of-prophylactic efficacy, darunavir, efavirenz, nevirapine, etravirine and rilpivirine could more potently prevent infection than existing PrEP regimen (Truvada). Notably, some drugs from this candidate set are patent-expired and currently neglected for PrEP repurposing. A next step is to further trim this candidate set by ruling out compounds with ominous safety profiles, to assess different administration schemes in silico and to test the remaining candidates in human trials.

Hybrid stochastic framework predicts efficacy of prophylaxis against HIV: An example with different dolutegravir prophylaxis schemes.

To achieve the 90-90-90 goals set by UNAIDS, the number of new HIV infections needs to decrease to approximately 500,000 by 2020. One of the 'five pillars' to achieve this goal is pre-exposure prophylaxis (PrEP). Truvada (emtricitabine-tenofovir) is currently the only medication approved for PrEP. Despite its advantages, Truvada is costly and requires individuals to adhere to the once-daily regimen. To improve PrEP, many next-generation regimen, including long-acting formulations, are currently investigated. However, pre-clinical testing may not guide candidate selection, since it often fails to translate into clinical efficacy. On the other hand, quantifying prophylactic efficacy in the clinic is ethically problematic and requires to conduct long (years) and large (N>1000 individuals) trials, precluding systematic evaluation of candidates and deployment strategies. To prioritize- and help design PrEP regimen, tools are urgently needed that integrate pharmacological-, viral- and host factors determining prophylactic efficacy. Integrating the aforementioned factors, we developed an efficient and exact stochastic simulation approach to predict prophylactic efficacy, as an example for dolutegravir (DTG). Combining the population pharmacokinetics of DTG with the stochastic framework, we predicted that plasma concentrations of 145.18 and 722.23nM prevent 50- and 90% sexual transmissions respectively. We then predicted the reduction in HIV infection when DTG was used in PrEP, PrEP 'on demand' and post-exposure prophylaxis (PEP) before/after virus exposure. Once daily PrEP with 50mg oral DTG prevented 99-100% infections, and 85% of infections when 50% of dosing events were missed. PrEP 'on demand' prevented 79-84% infections and PEP >80% when initiated within 6 hours after virus exposure and continued for as long as possible. While the simulation framework can easily be adapted to other PrEP candidates, our simulations indicated that oral 50mg DTG is non-inferior to Truvada. Moreover, the predicted 90% preventive concentrations can guide release kinetics of currently developed DTG nano-formulations.

Optimal Treatment Strategies in the Context of 'Treatment for Prevention' against HIV-1 in Resource-Poor Settings.

An estimated 2.7 million new HIV-1 infections occurred in 2010. `Treatment-for-prevention' may strongly prevent HIV-1 transmission. The basic idea is that immediate treatment initiation rapidly decreases virus burden, which reduces the number of transmittable viruses and thereby the probability of infection. However, HIV inevitably develops drug resistance, which leads to virus rebound and nullifies the effect of `treatment-for-prevention' for the time it remains unrecognized. While timely conducted treatment changes may avert periods of viral rebound, necessary treatment options and diagnostics may be lacking in resource-constrained settings. Within this work, we provide a mathematical platform for comparing different treatment paradigms that can be applied to many medical phenomena. We use this platform to optimize two distinct approaches for the treatment of HIV-1: (i) a diagnostic-guided treatment strategy, based on infrequent and patient-specific diagnostic schedules and (ii) a pro-active strategy that allows treatment adaptation prior to diagnostic ascertainment. Both strategies are compared to current clinical protocols (standard of care and the HPTN052 protocol) in terms of patient health, economic means and reduction in HIV-1 onward transmission exemplarily for South Africa. All therapeutic strategies are assessed using a coarse-grained stochastic model of within-host HIV dynamics and pseudo-codes for solving the respective optimal control problems are provided. Our mathematical model suggests that both optimal strategies (i)-(ii) perform better than the current clinical protocols and no treatment in terms of economic means, life prolongation and reduction of HIV-transmission. The optimal diagnostic-guided strategy suggests rare diagnostics and performs similar to the optimal pro-active strategy. Our results suggest that 'treatment-for-prevention' may be further improved using either of the two analyzed treatment paradigms.

NT-proBNP Qualifies as a Surrogate for Clinical End Points in Heart Failure.

N-terminal pro-B-type natriuretic peptide (NT-proBNP) is a well-established biomarker in heart failure (HF) but controversially discussed as a potential surrogate marker in HF trials. We analyzed the NT-proBNP/mortality relationship in real-world data (RWD) of 108,330 HF patients from the IBM Watson Health Explorys database and compared it with the NT-proBNP / clinical event end-point relationship in 20 clinical HF studies. With a hierarchical statistical model, we quantified the functional relationship and interstudy variability. To independently qualify the model, we predicted outcome hazard ratios in five phase III HF studies solely based on NT-proBNP measured early in the respective study. In RWD and clinical studies, the relationship between NT-proBNP and clinical outcome is well described by an Emax model. The NT-proBNP independent baseline risk (R0 , RWD/studies median (interstudy interquartile range): 5.5%/3.0% (1.7-4.9%)) is very low compared with the potential NT-proBNP-associated maximum risk (Rmax : 55.2%/79.4% (61.5-89.0%)). The NT-proBNP concentration associated with the half-maximal risk is comparable in RWD and across clinical studies (EC50 : 3,880/2,414 pg/mL (1,460-4,355 pg/mL)). Model-based predictions of phase III outcomes, relying on short-term NT-proBNP data only, match final trial results with comparable confidence intervals. Our analysis qualifies NT-proBNP as a surrogate for clinical outcome in HF trials. NT-proBNP levels after short treatment durations of less than 10 weeks quantitatively predict hazard ratios with confidence levels comparable to final trial readout. Early NT-proBNP measurement can therefore enable shorter and smaller but still reliable HF trials.

The Utility of Efavirenz-based Prophylaxis Against HIV Infection. A Systems Pharmacological Analysis.

Pre-exposure prophylaxis (PrEP) is considered one of the five "pillars" by UNAIDS to reduce HIV transmission. Moreover, it is a tool for female self-protection against HIV, making it highly relevant to sub-Saharan regions, where women have the highest infection burden. To date, Truvada is the only medication for PrEP. However, the cost of Truvada limits its uptake in resource-constrained countries. Similarly, several currently investigated, patent-protected compounds may be unaffordable in these regions. We set out to explore the potential of the patent-expired antiviral efavirenz (EFV) as a cost-efficient PrEP alternative. A population pharmacokinetic model utilizing data from the ENCORE1 study was developed. The model was refined for metabolic autoinduction. We then explored EFV cellular uptake mechanisms, finding that it is largely determined by plasma protein binding. Next, we predicted the prophylactic efficacy of various EFV dosing schemes after exposure to HIV using a stochastic simulation framework. We predicted that plasma concentrations of 11, 36, 1287 and 1486ng/mL prevent 90% sexual transmissions with wild type and Y181C, K103N and G190S mutants, respectively. Trough concentrations achieved after 600 mg once daily dosing (median: 2017 ng/mL, 95% CI:445-9830) and after reduced dose (400 mg) efavirenz (median: 1349ng/mL, 95% CI: 297-6553) provided complete protection against wild-type virus and the Y181C mutant, and median trough concentrations provided about 90% protection against the K103N and G190S mutants. As reduced dose EFV has a lower toxicity profile, we predicted the reduction in HIV infection when 400 mg EFV-PrEP was poorly adhered to, when it was taken "on demand" and as post-exposure prophylaxis (PEP). Once daily EFV-PrEP provided 99% protection against wild-type virus, if ≥50% of doses were taken. PrEP "on demand" provided complete protection against wild-type virus and prevented ≥81% infections in the mutants. PEP could prevent >98% infection with susceptible virus when initiated within 24 h after virus exposure and continued for at least 9 days. We predict that 400 mg oral EFV may provide superior protection against wild-type HIV. However, further studies are warranted to evaluate EFV as a cost-efficient alternative to Truvada. Predicted prophylactic concentrations may guide release kinetics of EFV long-acting formulations for clinical trial design.

Top-down and bottom-up modeling in system pharmacology to understand clinical efficacy: An example with NRTIs of HIV-1.

A major aim of Systems Pharmacology is to understand clinically relevant mechanisms of action (MOA) of drugs and to use this knowledge in order to optimize therapy. To enable this mission it is necessary to obtain knowledge on how in vitro testable insights translate into clinical efficacy. Mathematical modeling and data integration are essential components to achieve this goal. Two modeling philosophies are prevalent, each of which in isolation is not sufficient to achieve the above described: In a 'top-down' approach, a minimal pharmacokinetic-pharmacodynamic (PK-PD) model is derived from- and fitted to available clinical data. This model may lack interpretability in terms of mechanisms and may only be predictive for scenarios already covered by the data used to derive it. A 'bottom-up' approach builds on mechanistic insights derived from in vitro/ex vivo experiments, which can be conducted under controlled conditions, but may not be fully representative for the in vivo/clinical situation. In this work, we employ both approaches side-by-side to predict the clinical potency (IC50 values) of the nucleoside reverse transcriptase inhibitors (NRTIs) lamivudine, emtricitabine and tenofovir. In the 'top-down' approach, this requires to establish the dynamic link between the intracellularly active NRTI-triphosphates (which exert the effect) and plasma prodrug PK and to subsequently link this composite PK model to viral kinetics. The 'bottom-up' approach assesses inhibition of reverse transcriptase-mediated viral DNA polymerization by the intracellular, active NRTI-triphosphates, which has to be brought into the context of target cell infection. By using entirely disparate sets of data to derive and parameterize the respective models, our approach serves as a means to assess the clinical relevance of the 'bottom-up' approach. We obtain very good qualitative and quantitative agreement between 'top-down' vs. 'bottom-up' predicted IC50 values, arguing for the validity of the 'bottom-up' approach. We noted, however, that the 'top-down' approach is strongly dependent on the sparse and noisy intracellular pharmacokinetic data. All in all, our work provides confidence that we can translate in vitro parameters into measures of clinical efficacy using the 'bottom-up' approach. This may allow to infer the potency of various NRTIs in inhibiting e.g. mutant viruses, to distinguish sources of interaction of NRTI combinations and to assess the efficacy of different NRTIs for repurposing, e.g. for pre-exposure prophylaxis.

Pharmacokinetics and pharmacodynamics of the reverse transcriptase inhibitor tenofovir and prophylactic efficacy against HIV-1 infection.

Antiviral pre-exposure prophylaxis (PrEP) through daily drug administration can protect healthy individuals from HIV-1 infection. While PrEP was recently approved by the FDA, the potential long-term consequences of PrEP implementation remain entirely unclear. The aim of this study is to predict the efficacy of different prophylactic strategies with the pro-drug tenofovir-disoproxil-fumarate (TDF) and to assess the sensitivity towards timing- and mode of TDF administration (daily- vs. single dose), adherence and the number of transmitted viruses. We developed a pharmacokinetic model for TDF and its active anabolite tenofovir-diphosphate (TFV-DP) and validated it with data from 4 different trials, including 4 distinct dosing regimes. Pharmacokinetics were coupled to an HIV model and viral decay following TDF mono-therapy was predicted, consistent with available data. Subsequently, a stochastic approach was used to estimate the % infections prevented by (i) daily TDF-based PrEP, (ii) one week TDF started either shortly before, or -after viral exposure and (iii) a single dose oral TDF before viral challenge (sd-PrEP). Analytical solutions were derived to assess the relation between intracellular TFV-DP concentrations and prophylactic efficacy. The predicted efficacy of TDF was limited by a slow accumulation of active compound (TFV-DP) and variable TFV-DP half-life and decreased with increasing numbers of transmitted viruses. Once daily TDF-based PrEP yielded [Formula: see text]80% protection, if at least 40% of pills were taken. Sd-PrEP with 300 mg or 600 mg TDF could prevent [Formula: see text]50% infections, when given at least before virus exposure. The efficacy dropped to [Formula: see text]10%, when given 1 h before 24 h exposure. Efficacy could not be increased with increasing dosage or prolonged administration. Post-exposure prophylaxis poorly prevented infection. The use of drugs that accumulate more rapidly, or local application of tenofovir gel may overcome the need for drug administration long before virus exposure.