Improving the design and analysis of drug efficacy/effectiveness studies in malaria and in selected neglected tropical diseases (NTDs).

Infectious tropical diseases place an enormous burden on many human populations. The vast majority of such infections can be successfully treated and/or controlled by drugs so the continued provision of effective drugs is an essential component of medical provision in these settings. Such studies often take place in areas where mobile human populations and poor infrastructure mean that patient follow-up is challenging and often incomplete, and where high re-infection rates often obscure successful treatment outcomes. We argue that current methods of measuring drug efficacy/effectiveness in these settings could clearly be improved in a number of areas. We start by investigating an important paradigm species, falciparum malaria, which is one of the 'big three' infective killers, and then move onto the so-called 'neglected tropical diseases' with initial emphasis on shistosomes (a 'worm' infection spread by contact with water containing the snail intermediate hosts). We also consider how information on drug efficacy/effectiveness can be obtained from studies outside of formal drug clinical trials, such such as intermittent treatment programmes.

We shall investigate how accurately drug efficacy and effectiveness are measured in human tropical infectious diseases. The main methodological challenges are high levels of patient drop-out during follow-up after treatment, and high re-infection rates which mean that drug failures must be distinguished from new infections. We first investigate malaria as an important paradigm disease and then move on to other neglected tropical diseases (NTDs).

The basic technique will be to simulate field data appropriate for each disease and local epidemiological setting using our existing expertise in malaria drug treatment modelling and existing epidemiological models of NTDs. Drug efficacy/effectiveness can then be assessed using existing methods and compared to novel frequentist and Bayesian methods to be developed in the project. We can then address an equally important second question: are existing data collection protocols optimal, or could they be significantly improved? Specifically, how should the number of patients enrolled be balanced against intensity of drug follow-up, and would enrolling more patients with a less frequent, 'sparse' follow-up schedule provide better data while minimising the onus on individual patients for frequent and inconvenient follow up visits? We then consider how drug effectiveness can be monitored using data generated outside of standard clinical trials by following patients taking drugs either prescribed as standard first-line therapies, or administered during intermittent treatment programmes.

Impact will be achieved through four main classes of beneficiaries.

Academic researchers investigating drug efficacy/effectiveness and the impact of control programmes though mass drug administration.

Public health official will benefit through access to improved data. This will enable them to make better, evidence-based decisions on policies of fundamental importance to local populations. Typical situations may be to identify the most appropriate drug(s) to deploy locally, interpreting improved data from surveillance programmes designed to monitor and confirm their continued effectiveness, and deciding if, how and when to support local mass drug administration programmes.

Drug companies and organisations such as MMV (Medicines for Malaria Venture)and the DNDi (Drugs for Neglected Diseases initiative). The useful therapeutic lifespan of new drugs relies heavily on identifying robust drug regimens based on good quality design and analyse of clinical trials.

The ultimate beneficiaries will be patients living in areas where infectious tropical diseases are rife, and where provision of effective control programmes and access to effective anti-infective drugs are fundamental requirements.