Model-Informed Drug Development for Malaria Therapeutics

Oleuropein activates autophagy to circumvent anti-plasmodial defense

Antimalarial drug resistance and unavailability of effective vaccine warrant for newer drugs and drug targets. Hence, anti-inflammatory activity of phyto-compound (oleuropein; OLP) was determined in antigen (LPS)-stimulated human THP-1 macrophages (macrophage model of inflammation; MMI). Reduction in the inflammation was controlled by the PI3K-Akt1 signaling to establish the "immune-homeostasis." Also, OLP treatment influenced the cell death/autophagy axis leading to the modulated inflammation for extended cell survival. The findings with MII prompted us to detect the antimalarial activity of OLP in the wild type (3D7), D10-expressing GFP-Atg18 parasite, and chloroquine-resistant (Dd2) parasite. OLP did not show the parasite inhibition in the routine in vitro culture of P. falciparum whereas OLP increased the antimalarial activity of artesunate. The molecular docking of autophagy-related proteins, investigations with MMI, and parasite inhibition assays indicated that the host activated the autophagy to survive OLP pressure. The challenge model of P. berghei infection showed to induce autophagy for circumventing anti-plasmodial defenses.

In silico modeling revealed phytomolecules derived from Cymbopogon citratus (DC.) leaf extract as promising candidates for malaria therapy

The emergence of varying levels of resistance to currently available antimalarial drugs significantly threatens global health. This factor heightens the urgency to explore bioactive compounds from natural products with a view to discovering and developing newer antimalarial drugs with novel mode of actions. Therefore, we evaluated the inhibitory effects of sixteen phytocompounds from Cymbopogon citratus leaf extract against Plasmodium falciparum drug targets such as P. falciparum circumsporozoite protein (PfCSP), P. falciparum merozoite surface protein 1 (PfMSP1) and P. falciparum erythrocyte membrane protein 1 (PfEMP1). In silico approaches including molecular docking, pharmacophore modeling and 3D-QSAR were adopted to analyze the inhibitory activity of the compounds under consideration. The molecular docking results indicated that a compound swertiajaponin from C. citratus exhibited a higher binding affinity (-7.8 kcal/mol) to PfMSP1 as against the standard artesunate-amodiaquine (-6.6 kcal/mol). Swertiajaponin also formed strong hydrogen bond interactions with LYS29, CYS30, TYR34, ASN52, GLY55 and CYS28 amino acid residues. In addition, quercetin another compound from C. citratus exhibited significant binding energies -6.8 and -8.3 kcal/mol with PfCSP and PfEMP1, respectively but slightly lower than the standard artemether-lumefantrine with binding energies of -7.4 kcal/mol against PfCSP and -8.7 kcal/mol against PfEMP1. Overall, the present study provides evidence that swertiajaponin and other phytomolecules from C. citratus have modulatory properties toward P. falciparum drug targets and thus may warrant further exploration in early drug discovery efforts against malaria. Furthermore, these findings lend credence to the folkloric use of C. citratus for malaria treatment.Communicated by Ramaswamy H. Sarma.

Predicting bioequivalence and developing dissolution bioequivalence safe space in vitro for warfarin using a Physiologically-Based pharmacokinetic absorption model

OBJECTIVE

Bioequivalence (BE) studies support the approval and clinical use of both new and generic drug products. Narrow therapeutic index (NTI) drugs have relatively high costs and low success rates of BE evaluation clinical trials as high-risk drugs. A physiologically-based pharmacokinetic (PBPK) model can be used to evaluate the BE of two preparations.

METHODS

This study inputs the basic physical and chemical property parameters of warfarin sodium available at the present stage into GastroPlus™ software, and combined it with the Advanced Compartmental Absorption and Transit (ACAT™) model built into the software. The PBPK model of Chinese individuals taking 2.5 mg of warfarin sodium orally while fasted condition was developed using the disposal parameters calculated from the clinically measured PK data of the reference preparations. The model was tested using the PK data of other reference preparations and tested preparations from different domestic manufacturers.

RESULTS

The results revealed that at least 30% of drugs are released in 30 min under a pH of 4.5 condition, and at least 80% are released in 30 min under a pH of 6.8 condition, which can be used as bioequivalent dissolution limits under fasted conditions. The risk of BE failure in the fed condition will be significantly reduced for the clinical study on the BE of warfarin sodium, which is a NTI drug if the fasted condition is bioequivalent.

CONCLUSION

The results revealed that the PBPK models were successfully developed for 2.5 mg of warfarin sodium tablets in Chinese individuals. Developing a PBPK model for NTI drugs based on in vitro dissolution data in software is a promising method for BE evaluation, which can provide great help for developing new drugs and the clinical trial research of BE of generic drugs.

Evaluation of a multiphasic parasite clearance profile after treatment of experimental human infection with the investigational anti-malarial M5717 using segmented mixed effect models

BACKGROUND

Evaluation of parasite clearance patterns in experimental human infection trials helps increase understanding of drug action. In a previously reported phase Ib trial of a new investigational anti-malarial drug M5717, parasite clearance showed a biphasic linear pattern: slow removal phase with a near flat clearance rate followed by a fast clearance phase with a steep slope. In this study three statistical approaches were implemented and compared to estimate the parasite clearance rate for each phase and the time point corresponding to the change of clearance rates (changepoint between the two phases).

METHODS

Data using three M5717 doses 150 mg (n = 6), 400 mg (n = 8), 800 mg (n = 8) were used to estimate biphasic clearance rates. Three models were investigated: firstly, segmented mixed models with estimated changepoint-models with/without random effects in various parameters were compared. Secondly, a segmented mixed model using grid search-this method is similar to the first except that changepoints were not estimated, instead they were selected based on model fit from given candidate values. Thirdly, a two-stage approach whereby a segmented regression model fit to each participant followed by a meta-analysis method. Hourly rate of parasite clearance (HRPC) interpreted as the percentage of parasites removed each hour was calculated.

RESULTS

The three models generated similar results. Using segmented mixed models, the estimated changepoints after treatment in hours (95% CI) were: 150 mg: 33.9 (28.7, 39.1); 400 mg: 57.4 (52.5, 62.4); and 800 mg: 52.8 (47.4, 58.1). For all three treatment groups, there was nearly no clearance before the changepoints, but rapid clearance in the second phase (HRPC [95% CI]): 150 mg: 16.8% (14.3, 19.1%); 400 mg: 18.6% (16.0, 21.1%); and 800 mg: 11.7% (9.3, 14.1%).

CONCLUSIONS

All three statistical approaches are effective tools to characterize the bi-phasic clearance of M5717 in the phase 1b experimental Plasmodium falciparum malaria human infection study. The statistical approaches produced similar results to estimate the two-phase clearance rates and the changepoint for each treatment dose of M5717. However, the segmented mixed model with random changepoints has several advantages: it is computationally efficient, provides precision for changepoint estimates and is robust concerning outlying datapoints or individuals.

Drug discovery for parasitic diseases: powered by technology, enabled by pharmacology, informed by clinical science

While prevention is a bedrock of public health, innovative therapeutics are needed to complement the armamentarium of interventions required to achieve disease control and elimination targets for neglected diseases. Extraordinary advances in drug discovery technologies have occurred over the past decades, along with accumulation of scientific knowledge and experience in pharmacological and clinical sciences that are transforming many aspects of drug R&D across disciplines. We reflect on how these advances have propelled drug discovery for parasitic infections, focusing on malaria, kinetoplastid diseases, and cryptosporidiosis. We also discuss challenges and research priorities to accelerate discovery and development of urgently needed novel antiparasitic drugs.

Senna occidentalis (L.) Link root extract inhibits Plasmodium growth in vitro and in mice

BACKGROUND

Senna occidentalis (L.) Link has been used worldwide in traditional treatment of many diseases and conditions including snakebite. In Kenya, a decoction from the plant roots taken orally, is used as a cure for malaria. Several studies have demonstrated that extracts from the plant possess antiplasmodial activity, in vitro. However, the safety and curative potency of the plant root against established malaria infection is yet to be scientifically validated, in vivo. On the other hand, there are reports on variation in bioactivity of extracts obtained from this plant species, depending on the plant part used and place of origin among other factors. In this study, we demonstrated the antiplasmodial activity of Senna occidentalis roots extract in vitro, and in mice.

METHODS

Methanol, ethyl acetate, chloroform, hexane and water extracts of S. occidentalis root were tested for in vitro antiplasmodial activity against Plasmodium falciparum, strain 3D7. Cytotoxicity of the most active solvent extracts was determined using 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay and the curative potency in Plasmodium berghei infected mice evaluated by Rane's test.

RESULTS

All of the solvent extracts tested in this study inhibited the propagation of P. falciparum, strain 3D7, in vitro, with polar extracts being more active than non-polar ones. Methanolic extracts had the highest activity (IC50 = 1.76) while hexane extract displayed the lowest activity (IC50 = 18.47). At the tested concentrations, methanolic and aqueous extracts exhibited high selectivity index against P. falciparum strain 3D7 (SI > 10) in the cytotoxicity assay. Further, the extracts significantly suppressed the propagation of P. berghei parasites (P < 0.05) in vivo and increased the survival time of the infected mice (P < 0.0001).

CONCLUSIONS

Senna occidentalis (L.) Link root extract inhibits the propagation of malaria parasites in vitro and in BALB/c mice.

InfectionCMA: A Cell MicroArray Approach for Efficient Biomarker Screening in In Vitro Infection Assays

The recently emerged severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has forced the scientific community to acquire knowledge in real-time, when total lockdowns and the interruption of flights severely limited access to reagents as the global pandemic became established. This unique reality made researchers aware of the importance of designing efficient in vitro set-ups to evaluate infectious kinetics. Here, we propose a histology-based method to evaluate infection kinetics grounded in cell microarray (CMA) construction, immunocytochemistry and in situ hybridization techniques. We demonstrate that the chip-like organization of the InfectionCMA has several advantages, allowing side-by-side comparisons between diverse cell lines, infection time points, and biomarker expression and cytolocalization evaluation in the same slide. In addition, this methodology has the potential to be easily adapted for drug screening.

Evaluation of the antimalarial activity and toxicity of Mahanil-Tang-Thong formulation and its plant ingredients

Background

Novel potent antimalarial agents are urgently needed to overcome the problem of drug-resistant malaria. Herbal treatments are of interest because plants are the source of many pharmaceutical compounds. The Mahanil-Tang-Thong formulation is a Thai herbal formulation in the national list of essential medicines and is used for the treatment of fever. Therefore, this study aimed to evaluate the antimalarial activity of medicinal plants in the Mahanil-Tang-Thong formulation.

Methods

Nine medicinal plant ingredients of the Mahanil-Tang-Thong formulation were used in this study. Aqueous and ethanolic extracts of all the plants were analyzed for their phytochemical constituents. All the extracts were used to investigate the in vitro antimalarial activity against Plasmodium falciparum K1 (chloroquine-resistant strain) by using the lactate dehydrogenase (pLDH) method and cytotoxicity in Vero cells by using the 3-(4,5-dimethylthiazol2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay. Additionally, an extract with potent in vitro antimalarial activity and no toxicity was selected to determine the in vivo antimalarial activity with Peters’ 4-day suppressive test against the Plasmodium berghei ANKA strain. Acute toxicity was evaluated in mice for 14 days after the administration of a single oral dose of 2000 mg/kg.

Results

This study revealed that ethanolic extracts of Sapindus rarak DC., Tectona grandis L.f., Myristica fragrans Houtt. and Dracaena loureiri Gagnep. exhibited potent antimalarial activity, with half-maximal inhibitory concentration (IC50) values of 2.46, 3.21, 8.87 and 10.47 μg/ml, respectively, while the ethanolic of the formulation exhibited moderate activity with an IC50 value of 37.63 μg/ml and its aqueous extract had no activity (IC50 = 100.49 μg/ml). According to the in vitro study, the ethanolic wood extract of M. fragrans was selected for further investigation in an in vivo mouse model. M. fragrans extract at doses of 200, 400, and 600 mg/kg body weight produced a dose-dependent reduction in parasitemia by 8.59, 31.00, and 52.58%, respectively. No toxic effects were observed at a single oral dose of 2000 mg/kg body weight.

Conclusion

This study demonstrates that M. fragrans is a potential candidate for the development of antimalarial agents.

Systematic review on the application of machine learning to quantitative structure-activity relationship modeling against Plasmodium falciparum

Malaria accounts for over two million deaths globally. To flatten this curve, there is a need to develop new and high potent drugs against Plasmodium falciparum. Some major challenges include the dearth of suitable animal models for anti-P. falciparum assays, resistance to first-line drugs, lack of vaccines and the complex life cycle of Plasmodium. Gladly, newer approaches to antimalarial drug discovery have emerged due to the release of large datasets by pharmaceutical companies. This review provides insights into these new approaches to drug discovery covering different machine learning tools, which enhance the development of new compounds. It provides a systematic review on the use and prospects of machine learning in predicting, classifying and clustering IC₅₀ values of bioactive compounds against P. falciparum. The authors identified many machine learning tools yet to be applied for this purpose. However, Random Forest and Support Vector Machines have been extensively applied though on a limited dataset of compounds.

Willingness to pay for a hypothetical malaria vaccine in Brazil: a cross-sectional study and the implications

Aim: Malaria is an infection caused by protozoa of genus Plasmodium, considered the one associated with increasingly large outbreaks. Methods: A cross-sectional study was conducted with residents in the northern region of Brazil on the willingness to pay (WTP) for a hypothetical vaccine against malaria (effective protection of 80%). Results: Of 616 people interviewed, most interviewees were female (61%) and were employed (97%). The median individual maximum WTP for a hypothetical malaria vaccine was US$11.90 (BRL 50). Conclusion: The northern region of Brazil is one of the largest markets for a malaria vaccine due to its epidemiological relevance. Consequently, economic studies will be important to assist in the assessment of the potential price and value of new vaccines.

Cytochrome P450-Mediated Metabolism and CYP Inhibition for the Synthetic Peroxide Antimalarial OZ439

OZ439 is a potent synthetic ozonide evaluated for the treatment of uncomplicated malaria. The metabolite profile of OZ439 was characterized in vitro using human liver microsomes combined with LC/MS-MS, chemical derivatization, and metabolite synthesis. The primary biotransformations were monohydroxylation at the three distal carbon atoms of the spiroadamantane substructure, with minor contributions from N-oxidation of the morpholine nitrogen and deethylation cleavage of the morpholine ring. Secondary transformations resulted in the formation of dihydroxylation metabolites and metabolites containing both monohydroxylation and morpholine N-oxidation. With the exception of two minor metabolites, none of the other metabolites had appreciable antimalarial activity. Reaction phenotyping indicated that CYP3A4 is the enzyme responsible for the metabolism of OZ439, and it was found to inhibit CYP3A via both direct and mechanism-based inhibition. Elucidation of the metabolic pathways and kinetics will assist with efforts to predict potential metabolic drug-drug interactions and support physiologically based pharmacokinetic (PBPK) modeling.

Analytical validation of a real-time hydrolysis probe PCR assay for quantifying Plasmodium falciparum parasites in experimentally infected human adults

Background

Volunteer infection studies have become a standard model for evaluating drug efficacy against Plasmodium infections. Molecular techniques such as qPCR are used in these studies due to their ability to provide robust and accurate estimates of parasitaemia at increased sensitivity compared to microscopy. The validity and reliability of assays need to be ensured when used to evaluate the efficacy of candidate drugs in clinical trials.

Methods

A previously described 18S rRNA gene qPCR assay for quantifying Plasmodium falciparum in blood samples was evaluated. Assay performance characteristics including analytical sensitivity, reportable range, precision, accuracy and specificity were assessed using experimental data and data compiled from phase 1 volunteer infection studies conducted between 2013 and 2019. Guidelines for validation of laboratory-developed molecular assays were followed.

Results

The reportable range was 1.50 to 6.50 log₁₀ parasites/mL with a limit of detection of 2.045 log₁₀ parasites/mL of whole blood based on a parasite diluted standard series over this range. The assay was highly reproducible with minimal intra-assay (SD = 0.456 quantification cycle (C_q) units [0.137 log₁₀ parasites/mL] over 21 replicates) and inter-assay (SD = 0.604 C_q units [0.182 log₁₀ parasites/mL] over 786 qPCR runs) variability. Through an external quality assurance program, the QIMR assay was shown to generate accurate results (quantitative bias + 0.019 log₁₀ parasites/mL against nominal values). Specificity was 100% after assessing 164 parasite-free human blood samples.

Conclusions

The 18S rRNA gene qPCR assay is specific and highly reproducible and can provide reliable and accurate parasite quantification. The assay is considered fit for use in evaluating drug efficacy in malaria clinical trials.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12936-021-03717-y.

Model-Informed Drug Development for Anti-Infectives: State of the Art and Future

Model-informed drug development (MIDD) has a long and rich history in infectious diseases. This review describes foundational principles of translational anti-infective pharmacology, including choice of appropriate measures of exposure and pharmacodynamic (PD) measures, patient subpopulations, and drug-drug interactions. Examples are presented for state-of-the-art, empiric, mechanistic, interdisciplinary, and real-world evidence MIDD applications in the development of antibacterials (review of minimum inhibitory concentration-based models, mechanism-based pharmacokinetic/PD (PK/PD) models, PK/PD models of resistance, and immune response), antifungals, antivirals, drugs for the treatment of global health infectious diseases, and medical countermeasures. The degree of adoption of MIDD practices across the infectious diseases field is also summarized. The future application of MIDD in infectious diseases will progress along two planes; "depth" and "breadth" of MIDD methods. "MIDD depth" refers to deeper incorporation of the specific pathogen biology and intrinsic and acquired-resistance mechanisms; host factors, such as immunologic response and infection site, to enable deeper interrogation of pharmacological impact on pathogen clearance; clinical outcome and emergence of resistance from a pathogen; and patient and population perspective. In particular, improved early assessment of the emergence of resistance potential will become a greater focus in MIDD, as this is poorly mitigated by current development approaches. "MIDD breadth" refers to greater adoption of model-centered approaches to anti-infective development. Specifically, this means how various MIDD approaches and translational tools can be integrated or connected in a systematic way that supports decision making by key stakeholders (sponsors, regulators, and payers) across the entire development pathway.

An in vitro toolbox to accelerate anti-malarial drug discovery and development

Background

Modelling and simulation are being increasingly utilized to support the discovery and development of new anti-malarial drugs. These approaches require reliable in vitro data for physicochemical properties, permeability, binding, intrinsic clearance and cytochrome P450 inhibition. This work was conducted to generate an in vitro data toolbox using standardized methods for a set of 45 anti-malarial drugs and to assess changes in physicochemical properties in relation to changing target product and candidate profiles.

Methods

Ionization constants were determined by potentiometric titration and partition coefficients were measured using a shake-flask method. Solubility was assessed in biorelevant media and permeability coefficients and efflux ratios were determined using Caco-2 cell monolayers. Binding to plasma and media proteins was measured using either ultracentrifugation or rapid equilibrium dialysis. Metabolic stability and cytochrome P450 inhibition were assessed using human liver microsomes. Sample analysis was conducted by LC–MS/MS.

Results

Both solubility and fraction unbound decreased, and permeability and unbound intrinsic clearance increased, with increasing Log D_7.4. In general, development compounds were somewhat more lipophilic than legacy drugs. For many compounds, permeability and protein binding were challenging to assess and both required the use of experimental conditions that minimized the impact of non-specific binding. Intrinsic clearance in human liver microsomes was varied across the data set and several compounds exhibited no measurable substrate loss under the conditions used. Inhibition of cytochrome P450 enzymes was minimal for most compounds.

Conclusions

This is the first data set to describe in vitro properties for 45 legacy and development anti-malarial drugs. The studies identified several practical methodological issues common to many of the more lipophilic compounds and highlighted areas which require more work to customize experimental conditions for compounds being designed to meet the new target product profiles. The dataset will be a valuable tool for malaria researchers aiming to develop PBPK models for the prediction of human PK properties and/or drug–drug interactions. Furthermore, generation of this comprehensive data set within a single laboratory allows direct comparison of properties across a large dataset and evaluation of changing property trends that have occurred over time with changing target product and candidate profiles.

Nonlinear Mixed-Effects Model Development and Simulation Using nlmixr and Related R Open-Source Packages

nlmixr is a free and open-source R package for fitting nonlinear pharmacokinetic (PK), pharmacodynamic (PD), joint PK-PD, and quantitative systems pharmacology mixed-effects models. Currently, nlmixr is capable of fitting both traditional compartmental PK models as well as more complex models implemented using ordinary differential equations. We believe that, over time, it will become a capable, credible alternative to commercial software tools, such as NONMEM, Monolix, and Phoenix NLME.