Mush room for improving therapeutic approaches in psychiatry

Pharmacolog

The influence of drug distribution and drug-target binding on target occupancy: The rate-limiting step approximation

The influence of drug-target binding kinetics on target occupancy can be influenced by drug distribution and diffusion around the target, often referred to as "rebinding" or "diffusion-limited binding". This gives rise to a decreased decline of the drug-target complex concentration as a result of a locally higher drug concentration that arises around the target, which leads to prolonged target exposure to the drug. This phenomenon has been approximated by the steady-state approximation, assuming a steady-state concentration around the target. Recently, a rate-limiting step approximation of drug distribution and drug-target binding has been published. However, a comparison between both approaches has not been made so far. In this study, the rate-limiting step approximation has been rewritten into the same mathematical format as the steady-state approximation in order to compare the performance of both approaches for the investigation of the influence of drug-target binding kinetics on target occupancy. While both approximations clearly indicated the importance of kon and high target concentrations, it was shown that the rate-limiting step approximation is more accurate than the steady-state approximation, especially when dissociation is fast compared to association and distribution out of the binding compartment. It is therefore concluded that the new rate-limiting step approximation is to be preferred for assessing the influence of binding kinetics on local target site concentrations and target occupancy

The influence of drug distribution and drug-target binding on target occupancy: The rate-limiting step approximation

The influence of drug-target binding kinetics on target occupancy can be influenced by drug distribution and diffusion around the target, often referred to as "rebinding" or "diffusion-limited binding". This gives rise to a decreased decline of the drug-target complex concentration as a result of a locally higher drug concentration that arises around the target, which leads to prolonged target exposure to the drug. This phenomenon has been approximated by the steady-state approximation, assuming a steady-state concentration around the target. Recently, a rate-limiting step approximation of drug distribution and drug-target binding has been published. However, a comparison between both approaches has not been made so far. In this study, the rate-limiting step approximation has been rewritten into the same mathematical format as the steady-state approximation in order to compare the performance of both approaches for the investigation of the influence of drug-target binding kinetics on target occupancy. While both approximations clearly indicated the importance of kon and high target concentrations, it was shown that the rate-limiting step approximation is more accurate than the steady-state approximation, especially when dissociation is fast compared to association and distribution out of the binding compartment. It is therefore concluded that the new rate-limiting step approximation is to be preferred for assessing the influence of binding kinetics on local target site concentrations and target occupancy

Topics in Mathematical Pharmacology

Mathematical analysis of pharmacological models is becoming increasingly rel- evant for drug development. Emphasis on mechanistic models has grown and qualitative understanding of complex biological systems has improved a great deal. In this paper we present two examples of basic modular processes which are involved in a wide range of physiological systems. The first model concerns the interaction of a drug with its target, the way the compounds bind and then elicit an effect. The second model is central in signal trans- duction across the cell wall. Both models demonstrate the complex and interesting dynamics which is directly relevant for the impact of the drug. Analysis and Stochastic

Novel therapeutic modalities: the future is now

Pharmacolog

A review of quantitative systems pharmacology models of the coagulation cascade: opportunities for improved usability

Despite the numerous therapeutic options to treat bleeding or thrombosis, a comprehensive quantitative mechanistic understanding of the effects of these and potential novel therapies is lacking. Recently, the quality of quantitative systems pharmacology (QSP) models of the coagulation cascade has improved, simulating the interactions between proteases, cofactors, regulators, fibrin, and therapeutic responses under different clinical scenarios. We aim to review the literature on QSP models to assess the unique capabilities and reusability of these models. We systematically searched the literature and BioModels database reviewing systems biology (SB) and QSP models. The purpose and scope of most of these models are redundant with only two SB models serving as the basis for QSP models. Primarily three QSP models have a comprehensive scope and are systematically linked between SB and more recent QSP models. The biological scope of recent QSP models has expanded to enable simulations of previously unexplainable clotting events and the drug effects for treating bleeding or thrombosis. Overall, the field of coagulation appears to suffer from unclear connections between models and irreproducible code as previously reported. The reusability of future QSP models can improve by adopting model equations from validated QSP models, clearly documenting the purpose and modifications, and sharing reproducible code. The capabilities of future QSP models can improve from more rigorous validation by capturing a broader range of responses to therapies from individual patient measurements and integrating blood flow and platelet dynamics to closely represent in vivo bleeding or thrombosis risk.Pharmacolog

Predictions of bedaquiline and pretomanid target attainment in lung lesions of tuberculosis patients using translational minimal physiologically based pharmacokinetic modeling

BACKGROUND\nMETHODS\nRESULTS\nCONCLUSIONS\nSite-of-action concentrations for bedaquiline and pretomanid from tuberculosis patients are unavailable. The objective of this work was to predict bedaquiline and pretomanid site-of-action exposures using a translational minimal physiologically based pharmacokinetic (mPBPK) approach to understand the probability of target attainment (PTA).\nA general translational mPBPK framework for the prediction of lung and lung lesion exposure was developed and validated using pyrazinamide site-of-action data from mice and humans. We then implemented the framework for bedaquiline and pretomanid. Simulations were conducted to predict site-of-action exposures following standard bedaquiline and pretomanid, and bedaquiline once-daily dosing. Probabilities of average concentrations within lesions and lungs greater than the minimum bactericidal concentration for non-replicating (MBCNR) and replicating (MBCR) bacteria were calculated. Effects of patient-specific differences on target attainment were evaluated.\nThe translational modeling approach was successful in predicting pyrazinamide lung concentrations from mice to patients. We predicted that 94% and 53% of patients would attain bedaquiline average daily PK exposure within lesions (Cavg-lesion) > MBCNR during the extensive phase of bedaquiline standard (2 weeks) and once-daily (8 weeks) dosing, respectively. Less than 5% of patients were predicted to achieve Cavg-lesion > MBCNR during the continuation phase of bedaquiline or pretomanid treatment, and more than 80% of patients were predicted to achieve Cavg-lung >MBCR for all simulated dosing regimens of bedaquiline and pretomanid.\nThe translational mPBPK model predicted that the standard bedaquiline continuation phase and standard pretomanid dosing may not achieve optimal exposures to eradicate non-replicating bacteria in most patients.Pharmacolog

Model‐based dose optimization framework for bedaquiline, pretomanid, and linezolid for the treatment of drug‐resistant tuberculosis

AIM\nMETHODS\nRESULTS\nCONCLUSION\nBedaquiline, pretomanid, and linezolid combination (BPaL) treatment against Mycobacterium tuberculosis is promising yet safety and adherence concerns exist that motivates exploration of alternative dosing regimens. We developed a mechanistic modeling framework to compare the efficacy of the current and alternative BPaL treatment strategies.\nPharmacodynamic models for each drug in the BPaL combination treatment were developed using in vitro time-kill data. These models were combined with pharmacokinetic models, incorporating bodyweight, lesion volume, site-of-action distribution, bacterial susceptibility, and pharmacodynamic interactions to assemble the framework. The model was qualified by comparing the simulations against the observed clinical data. Simulations were performed evaluating bedaquiline and linezolid approved (bedaquiline 400mg once daily (QD) 14-days followed by 200mg three times a week, linezolid 1200mg QD) and alternative dosing regimens (bedaquiline 200mg QD, linezolid 600mg QD).\nThe framework adequately described the observed anti-bacterial activity data in patients following monotherapy for each drug and approved BPaL dosing. The simulations suggested a minor difference in median time to colony forming units (CFU)-clearance state with the bedaquiline alternative compared to the approved dosing and the linezolid alternative compared to the approved dosing. Median time to non-replicating-clearance state was predicted to be 15-days from the CFU-clearance state.\nThe model-based simulations suggested that comparable efficacy can be achieved using alternative bedaquiline and linezolid dosing, which may improve safety and adherence in drug-resistant tuberculosis patients. The framework can be utilized to evaluate treatment optimization approaches, including dosing regimen and duration of treatment predictions to eradicate both replicating- and non-replicating bacteria from lung and lesions.Pharmacolog