The implications of model-informed drug discovery and development for tuberculosis

Despite promising advances in the field and highly effective first-line treatment, an estimated 9.6 million people are still infected with tuberculosis (TB). Innovative methods are required to effectively transition the growing number of compounds into novel combination regimens. However, progression of compounds into patients occurs despite the lack of clear understanding of the pharmacokinetic–pharmacodynamic (PK/PD) relations. The PreDiCT-TB consortium was established in response to the existing gaps in TB drug development. The aim of the consortium is to develop new preclinical tools in concert with an in silico model-based approach, grounded in PKPD principles. Here, we highlight the potential impact of such an integrated framework on various stages in TB drug development and on the dose rationale for drug combinations

Discipline-Specific Compared to Generic Training of Teachers in Higher Education

A recurrent theme arising in the higher education sector is the suitability and effectiveness of generic versus discipline-specific training of university teachers, who are often recruited based on their disciplinary specialties to become teachers in higher education. We compared two groups of participants who had undergone training using a generic post-graduate certificate in higher education (PGCertGeneric) versus a discipline-specific course in veterinary education (PGCertVetEd). The study was conducted using a survey that allowed comparison of participants who completed PGCertGeneric (n=21) with PGCertVetEd (n=22). Results indicated that participants from both PGCertGeneric and PGCertVetEd considered teaching to be satisfying and important to their careers, valued the teaching observation component of the course, and identified similar training needs. However, the participants of the PGCertVetEd felt that the course made them better teachers, valued the relevance of the components taught, understood course design better, were encouraged to do further courses/reading in teaching and learning, changed their teaching as a result of the course, and were less stressed about teaching as compared to the PGCertGeneric participants (p<.05). It is likely that the PGCertVetEd, which was designed and developed by veterinarians with a wider understanding of the veterinary sector, helped the participants perceive the training course as suited to their needs

Growth dynamics and the evolution of cooperation in microbial populations

Microbes providing public goods are widespread in nature despite running the risk of being exploited by free-riders. However, the precise ecological factors supporting cooperation are still puzzling. Following recent experiments, we consider the role of population growth and the repetitive fragmentation of populations into new colonies mimicking simple microbial life-cycles. Individual-based modeling reveals that demographic fluctuations, which lead to a large variance in the composition of colonies, promote cooperation. Biased by population dynamics these fluctuations result in two qualitatively distinct regimes of robust cooperation under repetitive fragmentation into groups. First, if the level of cooperation exceeds a threshold, cooperators will take over the whole population. Second, cooperators can also emerge from a single mutant leading to a robust coexistence between cooperators and free-riders. We find frequency and size of population bottlenecks, and growth dynamics to be the major ecological factors determining the regimes and thereby the evolutionary pathway towards cooperation.Comment: 26 pages, 6 figure

Bounding Mean First Passage Times in Population Continuous-Time Markov Chains

We consider the problem of bounding mean first passage times and reachability probabilities for the class of population continuous-time Markov chains, which capture stochastic interactions between groups of identical agents. The quantitative analysis of such models is notoriously difficult since typically neither state-based numerical approaches nor methods based on stochastic sampling give efficient and accurate results. Here, we propose a novel approach that leverages techniques from martingale theory and stochastic processes to generate constraints on the statistical moments of first passage time distributions. These constraints induce a semi-definite program that can be used to compute exact bounds on reachability probabilities and mean first passage times without numerically solving the transient probability distribution of the process or sampling from it. We showcase the method on some test examples and tailor it to models exhibiting multimodality, a class of particularly challenging scenarios from biology

The Spread of Fecally Transmitted Parasites in Socially-Structured Populations

Mammals are infected by a wide array of gastrointestinal parasites, including parasites that also infect humans and domesticated animals. Many of these parasites are acquired through contact with infectious stages present in soil, feces or vegetation, suggesting that ranging behavior will have a major impact on their spread. We developed an individual-based spatial simulation model to investigate how range use intensity, home range overlap, and defecation rate impact the spread of fecally transmitted parasites in a population composed of social groups (i.e., a socially structured population). We also investigated the effects of epidemiological parameters involving host and parasite mortality rates, transmissibility, disease–related mortality, and group size. The model was spatially explicit and involved the spillover of a gastrointestinal parasite from a reservoir population along the edge of a simulated reserve, which was designed to mimic the introduction pathogens into protected areas. Animals ranged randomly within a “core” area, with biased movement toward the range center when outside the core. We systematically varied model parameters using a Latin hypercube sampling design. Analyses of simulation output revealed a strong positive association between range use intensity and the prevalence of infection. Moreover, the effects of range use intensity were similar in magnitude to effects of group size, mortality rates, and the per-contact probability of transmission. Defecation rate covaried positively with gastrointestinal parasite prevalence. Greater home range overlap had no positive effects on prevalence, with a smaller core resulting in less range overlap yet more intensive use of the home range and higher prevalence. Collectively, our results reveal that parasites with fecal-oral transmission spread effectively in socially structured populations. Future application should focus on parameterizing the model with empirically derived ranging behavior for different species or populations and data on transmission characteristics of different infectious organisms

Evolution with Stochastic Fitness and Stochastic Migration

Migration between local populations plays an important role in evolution - influencing local adaptation, speciation, extinction, and the maintenance of genetic variation. Like other evolutionary mechanisms, migration is a stochastic process, involving both random and deterministic elements. Many models of evolution have incorporated migration, but these have all been based on simplifying assumptions, such as low migration rate, weak selection, or large population size. We thus have no truly general and exact mathematical description of evolution that incorporates migration.We derive an exact equation for directional evolution, essentially a stochastic Price equation with migration, that encompasses all processes, both deterministic and stochastic, contributing to directional change in an open population. Using this result, we show that increasing the variance in migration rates reduces the impact of migration relative to selection. This means that models that treat migration as a single parameter tend to be biassed - overestimating the relative impact of immigration. We further show that selection and migration interact in complex ways, one result being that a strategy for which fitness is negatively correlated with migration rates (high fitness when migration is low) will tend to increase in frequency, even if it has lower mean fitness than do other strategies. Finally, we derive an equation for the effective migration rate, which allows some of the complex stochastic processes that we identify to be incorporated into models with a single migration parameter.As has previously been shown with selection, the role of migration in evolution is determined by the entire distributions of immigration and emigration rates, not just by the mean values. The interactions of stochastic migration with stochastic selection produce evolutionary processes that are invisible to deterministic evolutionary theory

Evaluation of high-dose rifampin in patients with new, smear-positive tuberculosis (HIRIF): study protocol for a randomized controlled trial.

BACKGROUND: Evidence has existed for decades that higher doses of rifampin may be more effective, but potentially more toxic, than standard doses used in tuberculosis treatment. Whether increased doses of rifampin could safely shorten treatment remains an open question. METHODS/DESIGN: The HIRIF study is a phase II randomized trial comparing rifampin doses of 20 and 15 mg/kg/day to the standard 10 mg/kg/day for the first 2 months of tuberculosis treatment. All participants receive standard doses of companion drugs and a standard continuation-phase treatment (4 months, 2 drugs). They are followed for 6 months post treatment. Study participants are adults with newly diagnosed, previously untreated, smear positive (≥2+) pulmonary tuberculosis. The primary outcome is rifampin area under the plasma concentration-time curve (AUC0-24) after at least 14 days of study treatment/minimum inhibitory concentration. 180 randomized participants affords 90 % statistical power to detect a difference of at least 14 mcg/mL*hr between the 20 mg/kg group and the 10 mg/kg group, assuming a loss to follow-up of up to 17 %. DISCUSSION: Extant evidence suggests the potential for increased doses of rifampin to shorten tuberculosis treatment duration. Early studies that explored this potential using intermittent, higher dosing were derailed by toxicity. Given the continued large, global burden of tuberculosis with nearly 10 million new cases annually, shortened regimens with existing drugs would offer an important advantage to patients and health systems. TRIAL REGISTRATION: This trial was registered with clinicaltrials.gov (registration number: NCT01408914 ) on 2 August 2011

Confidence from uncertainty - A multi-target drug screening method from robust control theory

<p>Abstract</p> <p>Background</p> <p>Robustness is a recognized feature of biological systems that evolved as a defence to environmental variability. Complex diseases such as diabetes, cancer, bacterial and viral infections, exploit the same mechanisms that allow for robust behaviour in healthy conditions to ensure their own continuance. Single drug therapies, while generally potent regulators of their specific protein/gene targets, often fail to counter the robustness of the disease in question. Multi-drug therapies offer a powerful means to restore disrupted biological networks, by targeting the subsystem of interest while preventing the diseased network from reconciling through available, redundant mechanisms. Modelling techniques are needed to manage the high number of combinatorial possibilities arising in multi-drug therapeutic design, and identify synergistic targets that are robust to system uncertainty.</p> <p>Results</p> <p>We present the application of a method from robust control theory, Structured Singular Value or μ- analysis, to identify highly effective multi-drug therapies by using robustness in the face of uncertainty as a new means of target discrimination. We illustrate the method by means of a case study of a negative feedback network motif subject to parametric uncertainty.</p> <p>Conclusions</p> <p>The paper contributes to the development of effective methods for drug screening in the context of network modelling affected by parametric uncertainty. The results have wide applicability for the analysis of different sources of uncertainty like noise experienced in the data, neglected dynamics, or intrinsic biological variability.</p

Antibacterial resistance and their genetic location in MRSA isolated in Kuwait hospitals, 1994-2004

BACKGROUND: Methicillin-resistant Staphylococcus aureus (MRSA) continues to be a major cause of serious infections in hospitals and in the community worldwide. In this study, MRSA isolated from patients in Kuwait hospitals were analyzed for resistance trends and the genetic location of their resistance determinants. METHODS: Between April 1994 and December 2004, 5644 MRSA isolates obtained from different clinical samples were studied for resistance to antibacterial agents according to guidelines from the National Committee for Clinical Laboratory Standards and the British Society for Antimicrobial Chemotherapy. The genetic location of their resistance determinants was determined by curing and transfer experiments. RESULTS: They were resistant to aminoglycosides, erythromycin, tetracycline, trimethoprim, fusidic acid, ciprofloxacin, chloramphenicol, rifampicin, mupirocin, cadmium acetate, mercuric chloride, propamidine isethionate and ethidium bromide but susceptible to vancomycin, teicoplanin and linezolid. The proportion of the isolates resistant to erythromycin, ciprofloxacin and fusidic acid increased during the study period. In contrast, the proportion of isolates resistant to gentamicin, tetracycline, chloramphenicol and trimethoprim declined. High-level mupirocin resistance increased rapidly from 1996 to 1999 and then declined. They contained plasmids of 1.9, 2.8, 3.0, 4.4, 27 and 38 kilobases. Genetic studies revealed that they carried plasmid-borne resistance to high-level mupirocin resistance (38 kb), chloramphenicol (2.8 – 4.4 kb), erythromycin (2.8–3.0 kb) and cadmium acetate, mercuric chloride, propamidine isethionate and ethidium bromide (27 kb) and chromosomal location for methicillin, the aminoglycosides, tetracycline, fusidic acid, ciprofloxacin and trimethoprim resistance. Thus, the 27 kb plasmids had resistance phenotypes similar to plasmids reported in MRSA isolates in South East Asia. CONCLUSION: The prevalence of resistance to erythromycin, ciprofloxacin, high-level mupirocin and fusidic acid increased whereas the proportion of isolates resistant to gentamicin, tetracycline, chloramphenicol and trimethoprim declined during the study period. They contained 27-kb plasmids encoding resistance to cadmium acetate, mercuric chloride, propamidine isethionate and ethidium bromide similar to plasmids isolated in MRSA from South East Asia. Molecular typing of these isolates will clarify their relationship to MRSA from South East Asia