- Drug interaction concerns may affect HIV treatment adherence among transgender women
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- Drug Interactions in Infectious Diseases | Journal of Antimicrobial Chemotherapy | Oxford Academic
- Participants apprehensive about combining HIV medications, hormones
Drug interactions can be the most unimaginative and uninteresting sets of information health professionals can review, and usually end up as a list of interactions that leave the reader to make their own judgement on appropriateness of what is presented and relevance to professional practice. Mechanisms of interaction do not often excite the reader since it is a recap of undergraduate material. However, what an enormous pleasure it has been to read a book that keeps you interested and motivated, and pushes you to further identify and explore the reference materials.
This book is an excellent review of the drug interactions in infectious diseases. It is appropriately aimed at health practitioners at undergraduate level and also provides an excellent update for postgraduate students and practitioners. The text is very well organized, with two introductory chapters that firstly provide an overview to the Oxford University Press is a department of the University of Oxford.
It furthers the University's objective of excellence in research, scholarship, and education by publishing worldwide. Sign In or Create an Account. Sign In. Advanced Search. Article Navigation. Close mobile search navigation Article Navigation. Volume Article Contents. Soraya Dhillon. Oxford Academic.
Google Scholar. This decrease in quinine concentrations was associated with a fivefold increase in reinfection compared with those patients only receiving quinine.flavdiawaiprotun.cf/finy-sexo-gratis.php
Drug interaction concerns may affect HIV treatment adherence among transgender women
These significant changes in exposure and subsequent treatment failures can be attributed to induction of CYP3A, evidenced by significantly higher metabolite exposure five fold increase in those taking rifampin. Concerns in coinfected populations are not solely limited to interactions between treatments for the infections, however. It cannot be assumed that the PK of either the victim or perpetrator compounds is consistent among healthy subjects, singly infected, and coinfected patients.
This unexplained decrease in exposure is not exclusive to rifampin. Conventionally considered as special populations in mainstream drug development, these populations in fact are target populations of product development in global health. Due to the paucity of data on both the expected PK and expected magnitude of DDIs in these patients from the inherent difficulties in conducting clinical research to collect such data, the potential risk almost always has to be extrapolated from healthy, nonpregnant adults in order to optimize dose selection.
Such extrapolation is not straightforward and is challenged by the lack of quantitative understanding of the unique physiology of these patients that may impact the PK and PD characteristics of both victim and perpetrator drugs. Treatment of TB in pregnant women is also not immune from this imbalance in research. Currently, the WHO does not recommend any changes in treatment protocol for pregnant women. These populations become more complex when coinfection exists. Similar changes in exposure have also been found for rifabutin, a rifampin alternative.
Similarly, DDIs with oral contraceptives has been a growing topic of research in recent years as oral contraceptives rely on a minimum concentration for efficacy and changes in exposure can result in treatment failure.
This resulted in concentrations falling below the minimum effective concentrations leading to an increased risk for unplanned pregnancies. Encouragingly, research into drug disposition and interactions in special populations has increased in recent years, which has led to enhanced understanding of the physiological component of a PBPK model for these populations virtual populations.
A panel of outcome measures, such as PK parameters for drug and metabolite, major PD end points, and safety observations should be evaluated and compiled. Furthermore, information on the inherent changes in patient physiology from these diseases that cannot be captured from healthy volunteers should be collected when available. These observations can be further refined using in vitro techniques when appropriate to determine the mechanism s behind the changes. Through modeling, preliminary predictions can be made for a specific population under various clinical scenarios, such as potential drug combinations, allowing for clinical studies to be prioritized so that resources are allocated to the most needed studies.
Depending on the confidence level of PBPK models, simulations can be used to support dosing recommendations in scenarios that cannot be informed by the conduct of clinical DDI studies, due to either ethical reasons or feasibility considerations. Understanding these DDIs is only part of the solution, however. The knowledge gained on these topics will then need to be translated to strategies that can be implemented in LIC communities.
Cooperative efforts in manufacturing additional dosage options and updated training for healthcare providers will need to be undertaken to ensure that the benefits from the ability to understand and predict DDIs are available to those who are at risk. Further research into these areas will also serve to complement related, ongoing efforts within the scientific community.
Together, these research activities enable researchers to capitalize on the existing and emerging knowledge in this field and allow the utilization of modeling and simulation methods to assess and manage complex DDIs in target populations of LICs. Better understanding the underlying conditions and the resultant changes in drug disposition in these populations will allow for the development of effective risk mitigation strategies when comedication is required.
A better understanding of comprehensive drug-related properties, population-specific attributes, such as physiological changes associated with infectious diseases, and the use of modeling and simulation techniques are discussed, as they can facilitate the implementation of optimal treatments for infectious diseases at the individual patient level. The snippet could not be located in the article text. This may be because the snippet appears in a figure legend, contains special characters or spans different sections of the article.
Clin Pharmacol Ther. Published online Mar PMID: Savannah J. Corresponding author.
Received Dec 18; Accepted Feb 3. Open in a separate window. Figure 1. Disease effect on drug PK Concerns in coinfected populations are not solely limited to interactions between treatments for the infections, however. Conflict of Interest The authors declared no competing interests for this work. References 1.
Drug Interactions in Infectious Diseases | Journal of Antimicrobial Chemotherapy | Oxford Academic
Dye C. After infectious diseases in a new era of health and development. B Biol. Holmes K. World Bank, Washington DC, US Food and Drug Administration. Duan J. Applications of population pharmacokinetics in current drug labelling. Zhao P. Wagner C. Zhang Z.
Drug Metab. De Sousa Mendes M. In FDA Appl. NDA Archary M. Lazzerini M. Antibiotics in severely malnourished children: systematic review of efficacy, safety and pharmacokinetics. World Health Organ.
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The World Health Organization. Global Tuberculosis Report WHO, Geneva, Switzerland, Treatment of Tuberculosis: Guidelines 4th edn, Vol. Tirona R. Vavricka S. Van, Ha H. Interactions of rifamycin SV and rifampicin with organic anion uptake systems of human liver. Hepatology 36 , — Parvez M. Comprehensive substrate characterization of 22 antituberculosis drugs for multiple solute carrier SLC uptake transporters in vitro. Agents Chemother. Dompreh A.
Participants apprehensive about combining HIV medications, hormones
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