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1.
Lancet HIV ; 8(1): e51-e58, 2021 01.
Artigo em Inglês | MEDLINE | ID: mdl-33271124

RESUMO

In light of the increasing global burden of new HIV infections, growing financial requirements, and shifting funding landscape, the global health community must accelerate the development and delivery of an HIV cure to complement existing prevention modalities. An effective curative intervention could prevent new infections, overcome the limitations of antiretroviral treatment, combat stigma and discrimination, and provide a sustainable financial solution for pandemic control. We propose steps to plan for an HIV cure now, including defining a target product profile and establishing the HIV Cure Africa Acceleration Partnership (HCAAP), a multidisciplinary public-private partnership that will catalyse and promote HIV cure research through diverse stakeholder engagement. HCAAP will convene stakeholders, including people living with HIV, at an early stage to accelerate the design, social acceptability, and rapid adoption of HIV-cure products.


Assuntos
Infecções por HIV/epidemiologia , HIV , Gerenciamento Clínico , Desenvolvimento de Medicamentos , Infecções por HIV/tratamento farmacológico , Infecções por HIV/prevenção & controle , Infecções por HIV/virologia , Pesquisas sobre Atenção à Saúde , Recursos em Saúde , Humanos , Parcerias Público-Privadas , Qualidade de Vida , Estigma Social , Fatores Socioeconômicos
2.
Lancet HIV ; 8(1): e42-e50, 2021 01.
Artigo em Inglês | MEDLINE | ID: mdl-33271125

RESUMO

Developing a cure for HIV is a global priority. Target product profiles are a tool commonly used throughout the drug development process to align interested parties around a clear set of goals or requirements for a potential product. Three distinct therapeutic modalities (combination therapies, ex-vivo gene therapy, and in-vivo gene therapy) for a target product profile for an HIV cure were identified. Using a process of expert face-to-face consultation and an online Delphi consultation, we found a high degree of agreement regarding the criteria for the optimum target product profile. Although the minimum attributes for a cure were debated, the broad consensus was that an acceptable cure need not be as safe and effective as optimally delivered antiretroviral therapy. An intervention that successfully cured a reasonable fraction of adults would be sufficient to advance to the clinic. These target product profiles will require further discussion and ongoing revisions as the field matures.


Assuntos
Infecções por HIV/epidemiologia , Terapia Antirretroviral de Alta Atividade , Terapia Combinada , Consenso , Gerenciamento Clínico , Prova Pericial , HIV , Infecções por HIV/tratamento farmacológico , Infecções por HIV/virologia , Humanos , Vigilância em Saúde Pública
3.
J Am Coll Radiol ; 17(1 Pt B): 165-170, 2020 Jan.
Artigo em Inglês | MEDLINE | ID: mdl-31918875

RESUMO

Radiologists today are under increasing work pressure. We surveyed radiologists in the United States across practice settings, and the overwhelming majority reported an increased workload. Artificial intelligence (AI), which includes machine learning, can help address these issues. It also has the potential to improve clinical outcomes and raise further the value of medical imaging in ways yet to be defined. In this article, we report on recent McKinsey & Company work to understand the growth of AI in medical imaging. We highlight progress in its clinical application, the investments that are backing it, and the barriers to broader adoption. We also offer a view on how the market will develop. AI is set to have a big impact on the medical imaging market and hence on how radiologists work, helping them to speed up scan time, make more accurate diagnoses, and ease their workload. As AI in medical imaging increasingly proves its worth, it is hard to imagine that AI will not ultimately transform radiology.


Assuntos
Inteligência Artificial , Diagnóstico por Imagem , Atitude Frente aos Computadores , Computação em Nuvem , Previsões , Humanos , Interpretação de Imagem Assistida por Computador , Processamento de Imagem Assistida por Computador , Investimentos em Saúde
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