Pharmacokinetics under the COVID-19 storm.
Identifieur interne : 000E66 ( Main/Exploration ); précédent : 000E65; suivant : 000E67Pharmacokinetics under the COVID-19 storm.
Auteurs : Venkatesh Pilla Reddy [Royaume-Uni] ; Eman El-Khateeb [Royaume-Uni, Égypte] ; Heeseung Jo [Royaume-Uni] ; Natalie Giovino [États-Unis] ; Emily Lythgoe [Royaume-Uni] ; Shringi Sharma [États-Unis] ; Weifeng Tang [États-Unis] ; Masoud Jamei [Royaume-Uni] ; Amin Rastomi-Hodjegan [Royaume-Uni]Source :
- British journal of clinical pharmacology [ 1365-2125 ] ; 2020.
Abstract
AIMS
The storm-like nature of the health crises caused by COVID-19 has led to unconventional clinical trial practices such as the relaxation of exclusion criteria. The question remains: how can we conduct diverse trials without exposing subgroups of populations to potentially harmful drug exposure levels? The aim of this study was to build a knowledge base of the effect of intrinsic/extrinsic factors on the disposition of several repurposed COVID-19 drugs.
METHODS
Physiologically based pharmacokinetic (PBPK) models were used to study the change in the pharmacokinetics (PK) of drugs repurposed for COVID-19 in geriatric patients, different race groups, organ impairment and drug-drug interactions (DDIs) risks. These models were also used to predict epithelial lining fluid (ELF) exposure, which is relevant for COVID-19 patients under elevated cytokine levels.
RESULTS
The simulated PK profiles suggest no dose adjustments are required based on age and race for COVID-19 drugs, but dose adjustments may be warranted for COVID-19 patients also exhibiting hepatic/renal impairment. PBPK model simulations suggest ELF exposure to attain a target concentration was adequate for most drugs, except for hydroxychloroquine, azithromycin, atazanavir and lopinavir/ritonavir.
CONCLUSION
We demonstrate that systematically collated data on absorption, distribution, metabolism and excretion, human PK parameters, DDIs and organ impairment can be used to verify simulated plasma and lung tissue exposure for drugs repurposed for COVID-19, justifying broader patient recruitment criteria. In addition, the PBPK model developed was used to study the effect of age and ethnicity on the PK of repurposed drugs, and to assess the correlation between lung exposure and relevant potency values from in vitro studies for SARS-CoV-2.
DOI: 10.1111/bcp.14668
PubMed: 33226664
PubMed Central: PMC7753415
Affiliations:
- Royaume-Uni, Égypte, États-Unis
- Angleterre, Grand Manchester, Massachusetts
- Boston, Manchester
- Université de Manchester
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first="Venkatesh" last="Pilla Reddy">Venkatesh Pilla Reddy</name><affiliation wicri:level="1"><nlm:affiliation>Modelling & Simulation, Early Oncology, R&D Oncology, AstraZeneca, Cambridge, UK.</nlm:affiliation><country xml:lang="fr">Royaume-Uni</country><wicri:regionArea>Modelling & Simulation, Early Oncology, R&D Oncology, AstraZeneca, Cambridge</wicri:regionArea><wicri:noRegion>Cambridge</wicri:noRegion></affiliation><affiliation wicri:level="1"><nlm:affiliation>Clinical Pharmacology and Quantitative Pharmacology, R&D, AstraZeneca, Cambridge, UK.</nlm:affiliation><country xml:lang="fr">Royaume-Uni</country><wicri:regionArea>Clinical Pharmacology and Quantitative Pharmacology, R&D, AstraZeneca, Cambridge</wicri:regionArea><wicri:noRegion>Cambridge</wicri:noRegion></affiliation></author><author><name sortKey="El Khateeb, Eman" sort="El Khateeb, Eman" uniqKey="El Khateeb E" first="Eman" last="El-Khateeb">Eman El-Khateeb</name><affiliation wicri:level="4"><nlm:affiliation>Centre for 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wicri:level="1"><nlm:affiliation>Modelling & Simulation, Early Oncology, R&D Oncology, AstraZeneca, Cambridge, UK.</nlm:affiliation><country xml:lang="fr">Royaume-Uni</country><wicri:regionArea>Modelling & Simulation, Early Oncology, R&D Oncology, AstraZeneca, Cambridge</wicri:regionArea><wicri:noRegion>Cambridge</wicri:noRegion></affiliation></author><author><name sortKey="Giovino, Natalie" sort="Giovino, Natalie" uniqKey="Giovino N" first="Natalie" last="Giovino">Natalie Giovino</name><affiliation wicri:level="3"><nlm:affiliation>Early Oncology Clinical, R&D Oncology, AstraZeneca, Boston, USA.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Early Oncology Clinical, R&D Oncology, AstraZeneca, Boston</wicri:regionArea><placeName><settlement type="city">Boston</settlement><region type="state">Massachusetts</region></placeName></affiliation></author><author><name sortKey="Lythgoe, Emily" sort="Lythgoe, Emily" uniqKey="Lythgoe E" first="Emily" last="Lythgoe">Emily Lythgoe</name><affiliation wicri:level="1"><nlm:affiliation>R&D Biopharmaceuticals, AstraZeneca, Cambridge, UK.</nlm:affiliation><country xml:lang="fr">Royaume-Uni</country><wicri:regionArea>R&D Biopharmaceuticals, AstraZeneca, Cambridge</wicri:regionArea><wicri:noRegion>Cambridge</wicri:noRegion></affiliation></author><author><name sortKey="Sharma, Shringi" sort="Sharma, Shringi" uniqKey="Sharma S" first="Shringi" last="Sharma">Shringi Sharma</name><affiliation wicri:level="1"><nlm:affiliation>Clinical Pharmacology and Quantitative Pharmacology, R&D, AstraZeneca, USA.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Clinical Pharmacology and Quantitative Pharmacology, R&D, AstraZeneca</wicri:regionArea><wicri:noRegion>AstraZeneca</wicri:noRegion></affiliation></author><author><name sortKey="Tang, Weifeng" sort="Tang, Weifeng" uniqKey="Tang W" first="Weifeng" last="Tang">Weifeng Tang</name><affiliation wicri:level="1"><nlm:affiliation>Clinical Pharmacology and Quantitative Pharmacology, R&D, AstraZeneca, USA.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Clinical Pharmacology and Quantitative Pharmacology, R&D, AstraZeneca</wicri:regionArea><wicri:noRegion>AstraZeneca</wicri:noRegion></affiliation></author><author><name sortKey="Jamei, Masoud" sort="Jamei, Masoud" uniqKey="Jamei M" first="Masoud" last="Jamei">Masoud Jamei</name><affiliation wicri:level="1"><nlm:affiliation>Certara UK Limited, Simcyp Division, Sheffield, UK.</nlm:affiliation><country xml:lang="fr">Royaume-Uni</country><wicri:regionArea>Certara UK Limited, Simcyp Division, Sheffield</wicri:regionArea><wicri:noRegion>Sheffield</wicri:noRegion></affiliation></author><author><name sortKey="Rastomi Hodjegan, Amin" sort="Rastomi Hodjegan, Amin" uniqKey="Rastomi Hodjegan A" first="Amin" last="Rastomi-Hodjegan">Amin Rastomi-Hodjegan</name><affiliation wicri:level="4"><nlm:affiliation>Centre for Applied Pharmacokinetic Research, University of Manchester, Manchester, UK.</nlm:affiliation><country xml:lang="fr">Royaume-Uni</country><wicri:regionArea>Centre for Applied Pharmacokinetic Research, University of Manchester, Manchester</wicri:regionArea><placeName><settlement type="city">Manchester</settlement><region type="country">Angleterre</region><region type="région" nuts="1">Grand Manchester</region></placeName><orgName type="university">Université de Manchester</orgName></affiliation><affiliation wicri:level="1"><nlm:affiliation>Certara UK Limited, Simcyp Division, Sheffield, UK.</nlm:affiliation><country xml:lang="fr">Royaume-Uni</country><wicri:regionArea>Certara UK Limited, Simcyp Division, Sheffield</wicri:regionArea><wicri:noRegion>Sheffield</wicri:noRegion></affiliation></author></analytic><series><title level="j">British journal of clinical pharmacology</title><idno type="eISSN">1365-2125</idno><imprint><date when="2020" type="published">2020</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><p><b>AIMS</b></p><p>The storm-like nature of the health crises caused by COVID-19 has led to unconventional clinical trial practices such as the relaxation of exclusion criteria. The question remains: how can we conduct diverse trials without exposing subgroups of populations to potentially harmful drug exposure levels? The aim of this study was to build a knowledge base of the effect of intrinsic/extrinsic factors on the disposition of several repurposed COVID-19 drugs.</p></div><div type="abstract" xml:lang="en"><p><b>METHODS</b></p><p>Physiologically based pharmacokinetic (PBPK) models were used to study the change in the pharmacokinetics (PK) of drugs repurposed for COVID-19 in geriatric patients, different race groups, organ impairment and drug-drug interactions (DDIs) risks. These models were also used to predict epithelial lining fluid (ELF) exposure, which is relevant for COVID-19 patients under elevated cytokine levels.</p></div><div type="abstract" xml:lang="en"><p><b>RESULTS</b></p><p>The simulated PK profiles suggest no dose adjustments are required based on age and race for COVID-19 drugs, but dose adjustments may be warranted for COVID-19 patients also exhibiting hepatic/renal impairment. PBPK model simulations suggest ELF exposure to attain a target concentration was adequate for most drugs, except for hydroxychloroquine, azithromycin, atazanavir and lopinavir/ritonavir.</p></div><div type="abstract" xml:lang="en"><p><b>CONCLUSION</b></p><p>We demonstrate that systematically collated data on absorption, distribution, metabolism and excretion, human PK parameters, DDIs and organ impairment can be used to verify simulated plasma and lung tissue exposure for drugs repurposed for COVID-19, justifying broader patient recruitment criteria. In addition, the PBPK model developed was used to study the effect of age and ethnicity on the PK of repurposed drugs, and to assess the correlation between lung exposure and relevant potency values from in vitro studies for SARS-CoV-2.</p></div></front></TEI><pubmed><MedlineCitation Status="Publisher" Owner="NLM"><PMID Version="1">33226664</PMID><DateRevised><Year>2021</Year><Month>01</Month><Day>15</Day></DateRevised><Article PubModel="Print-Electronic"><Journal><ISSN IssnType="Electronic">1365-2125</ISSN><JournalIssue CitedMedium="Internet"><PubDate><Year>2020</Year><Month>Nov</Month><Day>23</Day></PubDate></JournalIssue><Title>British journal of clinical pharmacology</Title><ISOAbbreviation>Br J Clin Pharmacol</ISOAbbreviation></Journal><ArticleTitle>Pharmacokinetics under the COVID-19 storm.</ArticleTitle><ELocationID EIdType="doi" ValidYN="Y">10.1111/bcp.14668</ELocationID><Abstract><AbstractText Label="AIMS" NlmCategory="OBJECTIVE">The storm-like nature of the health crises caused by COVID-19 has led to unconventional clinical trial practices such as the relaxation of exclusion criteria. The question remains: how can we conduct diverse trials without exposing subgroups of populations to potentially harmful drug exposure levels? The aim of this study was to build a knowledge base of the effect of intrinsic/extrinsic factors on the disposition of several repurposed COVID-19 drugs.</AbstractText><AbstractText Label="METHODS" NlmCategory="METHODS">Physiologically based pharmacokinetic (PBPK) models were used to study the change in the pharmacokinetics (PK) of drugs repurposed for COVID-19 in geriatric patients, different race groups, organ impairment and drug-drug interactions (DDIs) risks. These models were also used to predict epithelial lining fluid (ELF) exposure, which is relevant for COVID-19 patients under elevated cytokine levels.</AbstractText><AbstractText Label="RESULTS" NlmCategory="RESULTS">The simulated PK profiles suggest no dose adjustments are required based on age and race for COVID-19 drugs, but dose adjustments may be warranted for COVID-19 patients also exhibiting hepatic/renal impairment. PBPK model simulations suggest ELF exposure to attain a target concentration was adequate for most drugs, except for hydroxychloroquine, azithromycin, atazanavir and lopinavir/ritonavir.</AbstractText><AbstractText Label="CONCLUSION" NlmCategory="CONCLUSIONS">We demonstrate that systematically collated data on absorption, distribution, metabolism and excretion, human PK parameters, DDIs and organ impairment can be used to verify simulated plasma and lung tissue exposure for drugs repurposed for COVID-19, justifying broader patient recruitment criteria. In addition, the PBPK model developed was used to study the effect of age and ethnicity on the PK of repurposed drugs, and to assess the correlation between lung exposure and relevant potency values from in vitro studies for SARS-CoV-2.</AbstractText><CopyrightInformation>© 2020 British Pharmacological Society.</CopyrightInformation></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Pilla Reddy</LastName><ForeName>Venkatesh</ForeName><Initials>V</Initials><Identifier Source="ORCID">https://orcid.org/0000-0002-7786-4371</Identifier><AffiliationInfo><Affiliation>Modelling & Simulation, Early Oncology, R&D Oncology, AstraZeneca, Cambridge, UK.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Clinical Pharmacology and Quantitative Pharmacology, R&D, AstraZeneca, Cambridge, UK.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>El-Khateeb</LastName><ForeName>Eman</ForeName><Initials>E</Initials><Identifier Source="ORCID">https://orcid.org/0000-0002-8365-6528</Identifier><AffiliationInfo><Affiliation>Centre for Applied Pharmacokinetic Research, University of Manchester, Manchester, UK.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Clinical Pharmacy Department, Faculty of Pharmacy, Tanta University, Tanta, Egypt.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Jo</LastName><ForeName>Heeseung</ForeName><Initials>H</Initials><AffiliationInfo><Affiliation>Modelling & Simulation, Early Oncology, R&D Oncology, AstraZeneca, Cambridge, UK.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Giovino</LastName><ForeName>Natalie</ForeName><Initials>N</Initials><AffiliationInfo><Affiliation>Early Oncology Clinical, R&D Oncology, AstraZeneca, Boston, USA.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Lythgoe</LastName><ForeName>Emily</ForeName><Initials>E</Initials><AffiliationInfo><Affiliation>R&D Biopharmaceuticals, AstraZeneca, Cambridge, UK.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Sharma</LastName><ForeName>Shringi</ForeName><Initials>S</Initials><AffiliationInfo><Affiliation>Clinical Pharmacology and Quantitative Pharmacology, R&D, AstraZeneca, USA.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Tang</LastName><ForeName>Weifeng</ForeName><Initials>W</Initials><AffiliationInfo><Affiliation>Clinical Pharmacology and Quantitative Pharmacology, R&D, AstraZeneca, USA.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Jamei</LastName><ForeName>Masoud</ForeName><Initials>M</Initials><AffiliationInfo><Affiliation>Certara UK Limited, Simcyp Division, Sheffield, UK.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Rastomi-Hodjegan</LastName><ForeName>Amin</ForeName><Initials>A</Initials><AffiliationInfo><Affiliation>Centre for Applied Pharmacokinetic Research, University of Manchester, Manchester, UK.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Certara UK Limited, Simcyp Division, Sheffield, UK.</Affiliation></AffiliationInfo></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2020</Year><Month>11</Month><Day>23</Day></ArticleDate></Article><MedlineJournalInfo><Country>England</Country><MedlineTA>Br J Clin Pharmacol</MedlineTA><NlmUniqueID>7503323</NlmUniqueID><ISSNLinking>0306-5251</ISSNLinking></MedlineJournalInfo><CitationSubset>IM</CitationSubset><KeywordList Owner="NOTNLM"><Keyword MajorTopicYN="N">ADME</Keyword><Keyword MajorTopicYN="N">COVID-19</Keyword><Keyword MajorTopicYN="N">Drug-Drug Interactions</Keyword><Keyword MajorTopicYN="N">M&S</Keyword><Keyword MajorTopicYN="N">PBPK</Keyword><Keyword MajorTopicYN="N">PKPD</Keyword><Keyword MajorTopicYN="N">cytokine</Keyword></KeywordList></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="received"><Year>2020</Year><Month>06</Month><Day>26</Day></PubMedPubDate><PubMedPubDate PubStatus="revised"><Year>2020</Year><Month>10</Month><Day>26</Day></PubMedPubDate><PubMedPubDate PubStatus="accepted"><Year>2020</Year><Month>11</Month><Day>06</Day></PubMedPubDate><PubMedPubDate PubStatus="pubmed"><Year>2020</Year><Month>11</Month><Day>24</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="medline"><Year>2020</Year><Month>11</Month><Day>24</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="entrez"><Year>2020</Year><Month>11</Month><Day>23</Day><Hour>12</Hour><Minute>12</Minute></PubMedPubDate></History><PublicationStatus>aheadofprint</PublicationStatus><ArticleIdList><ArticleId IdType="pubmed">33226664</ArticleId><ArticleId IdType="doi">10.1111/bcp.14668</ArticleId><ArticleId IdType="pmc">PMC7753415</ArticleId></ArticleIdList><ReferenceList><Title>REFERENCES</Title><Reference><Citation>FDA. 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