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Using quantitative systems pharmacology to evaluate the drug efficacy of COX-2 and 5-LOX inhibitors in therapeutic situations.

ABSTRACT: A quantitative analysis of dose-response relationships is essential in preclinical and clinical drug development in order to optimize drug efficacy and safety, respectively. However, there is a lack of quantitative understanding about the dynamics of pharmacological drug-target interactions in biological systems. In this study, a quantitative systems pharmacology (QSP) approach is applied to quantify the drug efficacy of cyclooxygenase-2 (COX-2) and 5-lipoxygenase (5-LOX) inhibitors by coupling physiologically based pharmacokinetic models, at the whole-body level, with affected biological networks, at the cellular scale. Both COX-2 and 5-LOX are key enzymes in the production of inflammatory mediators and are known targets in the design of anti-inflammatory drugs. Drug efficacy is here evaluated for single and appropriate co-treatment of diclofenac, celecoxib, zileuton, and licofelone by quantitatively studying the reduction of prostaglandins and leukotrienes. The impact of rifampicin pre-treatment on prostaglandin formation is also investigated by considering pharmacokinetic drug interactions with diclofenac and celecoxib, finally suggesting optimized dose levels to compensate for the reduced drug action. Furthermore, a strong correlation was found between pain relief observed in patients as well as celecoxib- and diclofenac-induced decrease in prostaglandins after 6?h. The findings presented reveal insights about drug-induced modulation of cellular networks in a whole-body context, thereby describing complex pharmacokinetic/pharmacodynamic behavior of COX-2 and 5-LOX inhibitors in therapeutic situations. The results demonstrate the clinical benefit of using QSP to predict drug efficacy and, hence, encourage its use in future drug discovery and development programs.

SUBMITTER: Thiel C

PROVIDER: S-EPMC6072773 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Using quantitative systems pharmacology to evaluate the drug efficacy of COX-2 and 5-LOX inhibitors in therapeutic situations.

Thiel Christoph C Smit Ines I Baier Vanessa V Cordes Henrik H Fabry Brigida B Blank Lars Mathias LM Kuepfer Lars L

NPJ systems biology and applications 20180803

A quantitative analysis of dose-response relationships is essential in preclinical and clinical drug development in order to optimize drug efficacy and safety, respectively. However, there is a lack of quantitative understanding about the dynamics of pharmacological drug-target interactions in biological systems. In this study, a quantitative systems pharmacology (QSP) approach is applied to quantify the drug efficacy of cyclooxygenase-2 (COX-2) and 5-lipoxygenase (5-LOX) inhibitors by coupling ...[more]

PMID: 30083389

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Project description:The use of peptide-drug conjugates is emerging as a powerful strategy for targeted drug delivery. Previously, we have found that peptides conjugated to a non-steroidal anti-inflammatory drug (NSAID), more specifically naproxen-dehydrodipeptide conjugates, readily form nanostructured fibrilar supramolecular hydrogels. These hydrogels were revealed as efficacious nano-carriers for drug delivery applications. Moreover, the incorporation of superparamagnetic iron oxide nanoparticles (SPIONs) rendered the hydrogels responsive to external magnetic fields, undergoing gel-to-solution phase transition upon remote magnetic excitation. Thus, magnetic dehydrodipeptide-based hydrogels may find interesting applications as responsive Magnetic Resonance Imaging (MRI) contrast agents and for magnetic hyperthermia-triggered drug-release applications. Supramolecular hydrogels where the hydrogelator molecule is endowed with intrinsic pharmacological properties can potentially fulfill a dual function in drug delivery systems as (passive) nanocariers for incorporated drugs and as active drugs themselves. In this present study, we investigated the pharmacological activities of a panel of naproxen-dehydrodipeptide conjugates, previously studied for their hydrogelation ability and as nanocarriers for drug-delivery applications. A focused library of dehydrodipeptides, containing N-terminal canonical amino acids (Phe, Tyr, Trp, Ala, Asp, Lys, Met) N-capped with naproxen and linked to a C-terminal dehydroaminoacid (?Phe, ?Abu), were evaluated for their anti-inflammatory and anti-cancer activities, as well as for their cytotoxicity to non-cancer cells, using a variety of enzymatic and cellular assays. All compounds except one were able to significantly inhibit lipoxygenase (LOX) enzyme at a similar level to naproxen. One of the compounds 4 was able to inhibit the cyclooxygenase-2 (COX-2) to a greater extent than naproxen, without inhibiting cyclooxygenase-1 (COX-1), and therefore is a potential lead in the search for selective COX-2 inhibitors. This hydrogelator is a potential candidate for dual COX/LOX inhibition as an optimised strategy for treating inflammatory conditions.

Project description:BackgroundImmune checkpoint blockade therapy has clearly shown clinical activity in patients with triple-negative breast cancer, but less than half of the patients benefit from the treatments. While a number of ongoing clinical trials are investigating different combinations of checkpoint inhibitors and chemotherapeutic agents, predictive biomarkers that identify patients most likely to benefit remains one of the major challenges. Here we present a modular quantitative systems pharmacology (QSP) platform for immuno-oncology that incorporates detailed mechanisms of immune-cancer cell interactions to make efficacy predictions and identify predictive biomarkers for treatments using atezolizumab and nab-paclitaxel.MethodsA QSP model was developed based on published data of triple-negative breast cancer. With the model, we generated a virtual patient cohort to conduct in silico virtual clinical trials and make retrospective analyses of the pivotal IMpassion130 trial that led to the accelerated approval of atezolizumab and nab-paclitaxel for patients with programmed death-ligand 1 (PD-L1) positive triple-negative breast cancer. Available data from clinical trials were used for model calibration and validation.ResultsWith the calibrated virtual patient cohort based on clinical data from the placebo comparator arm of the IMpassion130 trial, we made efficacy predictions and identified potential predictive biomarkers for the experimental arm of the trial using the proposed QSP model. The model predictions are consistent with clinically reported efficacy endpoints and correlated immune biomarkers. We further performed a series of virtual clinical trials to compare different doses and schedules of the two drugs for simulated therapeutic optimization.ConclusionsThis study provides a QSP platform, which can be used to generate virtual patient cohorts and conduct virtual clinical trials. Our findings demonstrate its potential for making efficacy predictions for immunotherapies and chemotherapies, identifying predictive biomarkers, and guiding future clinical trial designs.

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Using quantitative systems pharmacology to evaluate the drug efficacy of COX-2 and 5-LOX inhibitors in therapeutic situations.

Publications

Using quantitative systems pharmacology to evaluate the drug efficacy of COX-2 and 5-LOX inhibitors in therapeutic situations.

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