MétaCan
Menu
Back to cohort

Grapefruit Juice Increases Bioavailability of mTOR Inhibitor; Turning a Problem with Oral Therapies into an Advantage

2012· article· en· W2328624403 on OpenAlexaboutno aff
Rabiya S. Tuma

Bibliographic record

VenueOncology Times · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPI3K/AKT/mTOR signaling in cancer
Canadian institutionsnot available
Fundersnot available
KeywordsKetoconazoleGrapefruit juiceBioavailabilityPharmacologySirolimusDrugPharmacokineticsMedicineInternal medicineDermatology

Abstract

fetched live from OpenAlex

ImageGrapefruit juice is known to interfere with the metabolism of numerous drugs, and patients on those drugs are often warned to avoid the fruit. Now, researchers at the University of Chicago have found a way to turn that disadvantage into an advantage for sirolimus, a commercially available mTOR inhibitor. If optimized, the approach could reduce drug costs for a wide variety of oral cancer agents, according to the study authors. “What has been perceived as a problem of drug-food interactions, we really saw as an opportunity to enhance the bioavailability of this drug, sirolimus, because we know that very little of it actually does get absorbed,” said lead author Ezra Cohen, MD, Associate Professor of Medicine at the University of Chicago Comprehensive Cancer Center. To test the juice's ability to increase drug bioavailability, Cohen and colleagues enrolled 138 patients with advanced cancer in one of three phase I trials. Patients in the trials received sirolimus, sirolimus plus ketoconazole, or sirolimus plus grapefruit juice.EZRA E.W. COHEN, MD: “The pathway that grapefruit juice inhibits is the main set of metabolizing enzymes for oral drugs—the CYP3A-cytochrome p450 pathway. Almost every oral oncology drug now on the market is metabolized through this pathway, and many, many more are in development.”Ketoconazole reduced the amount of drug required to reach the desired area under the concentration curve (AUC; 3,810 ng-h/ml) by 500 percent, whereas grapefruit juice reduced it by 350 percent. In absolute terms, the once weekly dose required to reach the target AUC was 16 mg for patients taking sirolimus plus ketoconazole, 25 mg for patients taking sirolimus plus grapefruit juice, and 90 mg for patients taking sirolimus alone. Despite the absolute differences in dosing, the researchers saw no significant differences in adverse events between the three drug regimens. Cohen acknowledges that there are challenges for developing grapefruit juice as a modifier of drug uptake. For example, the team's initial studies used an off-the-shelf type of grapefruit juice, which had minimal inhibitory effect on the metabolic enzymes. By contrast, freshly frozen juice was a potent inhibitor of the CYP3A enzyme and effectively increased the bioavailability of sirolimus. Therefore, grapefruit juice would need to be standardized and clear directions regarding storage and use provided to patients—similar to what is done for drugs themselves. Funding Another major hurdle is funding. The group has approached several government organizations, including Health Canada and the National Cancer Institute's Cancer Therapy Evaluation Program (CTEP), as well as a third-party payer, but have not yet found a group willing to support further development of the strategy. “There is no doubt that the development of these ideas is going to cost something,” Cohen told OT. “But if we look at it in the context of how much these drugs cost now, you see the cost savings quickly begin to be realized once the clinical trials are done. Many oral oncology drugs run at $5k per month, sometimes more. We have the potential to reduce the amount of drug needed by half—or in some cases, like sirolimus, by 60 to 70 percent.” Expanding Opportunity Although the current work, now available online ahead of print in Clinical Cancer Research (doi: 10.1158/1078–0432.CCR-12–0110), tests grapefruit juice's ability to affect the bioavailability of a single drug, Cohen and others emphasize that the principle also applies to other oral agents. “The pathway that grapefruit juice inhibits is the main set of metabolizing enzymes for oral drugs,” he said. “It is the CYP3A-cytochrome p450 pathway. Almost every oral oncology drug now on the market is metabolized through this pathway, and many, many more are in development.” Cohen also notes that the issue of drug-diet interaction is going to become a more pressing issue for oncologists, as more oral drugs come into the clinic: “In that sense, we've been spoiled in oncology because most of the agents we have administered are IV, so as medical oncologists we haven't had to worry about these things.” “Clearly now it is a much bigger issue,” he continued, pointing to an editorial he wrote with senior author Mark Ratain, MD, a few years ago about the impact of taking lapatinib with or without food (JCO 2007;25:3397–3398). “Some drugs need to be taken with food, some on an empty stomach, some can be taken with food, but you need to avoid fatty foods. So it is really something that as physicians we need to be educated in—and patients really need to adhere to the labels.” ‘Very Careful Implementation Needed’ Asked for his opinion, Jan Schellens, MD, PhD, Professor of Clinical Pharmacology at The Netherlands Cancer Institute in Amsterdam, who studies drug bioavailability, said he is enthusiastic but cautious about the approach. “Drs. Cohen and Ratain repeatedly make valid points,” he wrote in an email message. “Personally I am very much in favor of strategies to improve oral bioavailability. I believe variability will be reduced, therapy outcomes may improve, and costs may be reduced. “Whether one can standardize grapefruit juice intake or food to improve bioavailability in general practice needs additional studies and very careful implementation,” he continued. “It seems a simple ‘trick,’ but as with everything it may work well in the research environment but then turn out to be more complex in general practice.” Presented at ASCO and AACR Meetings Parts of the study were presented in abstract form at the 2006, 2007, and 2008 ASCO Annual Meetings as well as the 2009 AACR Annual Meeting.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.189
Threshold uncertainty score0.726

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.012
GPT teacher head0.294
Teacher spread0.283 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueOncology TimesSame topicPI3K/AKT/mTOR signaling in cancerFrench-language works237,207