Relationship between Human Milk Lipid-Ultrafiltrate and Octanol-Water Partition Coefficients

Atkinson, Helen C.; Begg, Evan J.

doi:10.1002/jps.2600770916

Cited by 47 publications

(23 citation statements)

References 16 publications

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“…Almost identical results are achieved when using a formula for logP app 7.2 calculated from logD(7) by the formula proposed by Atkinson and Begg in 1988. 3 This is not surprising, as the logP app at pH 7.2 is identical between the 2 methods of its estimation (r 2 = 0.99). Why is it so difficult to predict M/P ratios in humans?…”

supporting

confidence: 59%

Retraction: Acute Myelogenous Leukemia Following Mitoxantrone Treatment for Multiple Sclerosis

2004

Ann Pharmacother

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We thank Begg and colleagues and Ilett and Hackett for their comments. We are very pleased to extend the discussion on prediction of milk levels of drugs. As will be made clear soon, we have calculated M/P ratios in different ways, including the Begg's formula for logP app . Because our published paper unified 2 original papers, some of the calculations were done but not published and we are pleased to present them here. None of these permutations help to improve the predictive value of the model.At the Motherisk program in Toronto, we counsel up to 170 women daily on drug exposure in pregnancy and 30 women daily on drug use during lactation. For most of these drugs, there are no satisfactory experimental M/P ratios; hence, we are painfully aware of the need for a solid prediction model.The model created by Begg and colleagues in the 1980s was very appealing, as it used simple physicochemical properties available for most drugs. As a first critical step in validating any model, we had to identify a gold standard, that is, a list of drugs for which there are satisfactory experimental M/P ratios.1 It is important to note that most drugs used by Begg et al.2 to validate their model in 1992 do not have sufficient kinetic data fulfilling our criteria of gold standard.The results of the logP shown by us use a completely pH-independent constant. We of course also calculated logD at pH 7.2 using logD(7) and logD(8) from SciFinder and extrapolating it to pH 7.2. For basic drugs, the correlation between experimental versus predicted logD(7.2) values has an r value of 0.08. Most critically, the mean ± SD of the error of predicted versus experimental is 63.5% ± 109% (range 3-783%; median 39%). We further examined the precision of just predicted M/P values above unity (leaving out small M/P ratios where a big difference is clinically not important). Here too, the mean error is 90% ± 148% (14-783%; median 61%). The results for acidic drugs are even more disappointing: mean error 1247% ± 634% (median 1388%).Hence, while Begg and colleagues may describe a small list of drugs where their predicted M/P ratios are close to experimental data, when one looks at all 78 studies (69 drugs) where there are sufficient data on the gold standard M/P ratio, the predictive value is low. Almost identical results are achieved when using a formula for logP app 7.2 calculated from logD(7) by the formula proposed by Atkinson and Begg in 1988. 3 This is not surprising, as the logP app at pH 7.2 is identical between the 2 methods of its estimation (r 2 = 0.99). Why is it so difficult to predict M/P ratios in humans? First, it is becoming clear that the mammary epithelium has a large number of active transporters which, of course, work against simple physicochemical properties.4 Second, Begg et al. based their predictions on simulating the ability of milk lipid to bind and retain drugs. However, this does not resolve or necessarily reflect the ability of drugs to cross the lipid epithelial layer. Third, as shown above, most drugs used in the Atkinso...

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confidence: 59%

Retraction: Acute Myelogenous Leukemia Following Mitoxantrone Treatment for Multiple Sclerosis

2004

Ann Pharmacother

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“…After intravenous administration of cyclosporine in cremophor EL (0.5-3.5 mM) as Table 1 Major physicochemical and pharmacokinetic characteristics of digoxin and talinolol (Aronson 1980;Atkinson and Begg 1988;Caldwell and Cline 1976;Doherty et al 1969;Drescher et al 2003;Giessmann et al 2004a;Greiner et al 1999;Hinderling and Hartmann 1991;Iisalo 1977;Kurata et al 2002;Rengelshausen et al 2003;Schwarz et al 2007;Siegmund et al 2002a;Steiness 1974;Sumner and Russell 1976;Watson et al 1973;Westphal et al 2000a, b well as after infusion of quinidine (37.5 mg/kg min), the urinary recovery of digoxin was reduced by about 50% without change of renal blood flow or urine flow (both p < 0.001). The authors concluded that there is a luminally localized secretory system for digoxin in the kidneys .…”

Section: Affinity To P-glycoprotein In Vitro and In Animal Studiesmentioning

confidence: 98%

In Vivo Probes of Drug Transport: Commonly Used Probe Drugs to Assess Function of Intestinal P-glycoprotein (ABCB1) in Humans

Oswald

Terhaag

Siegmund

2010

Handbook of Experimental Pharmacology

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Intestinal P-glycoprotein (P-gp, ABCB1) may significantly influence drug absorption and elimination. Its expression and function is highly variable, regio-selective and influenced by genetic polymorphisms, drug interactions and intestinal diseases. An in vivo probe drug for intestinal P-gp should a registered, safe and well tolerated nonmetabolized selective substrate with low protein binding for which P-gp is rate-limiting during absorption. Other P-gp dependent processes should be of minor influence. The mechanism(s) and kinetics of intestinal uptake must be identified and quantified. Moreover, the release properties of the dosage form should be known. So far, the cardiac glycoside digoxin and the ß₁-selective blocker talinolol have been used in mechanistic clinical studies, because they meet most of these criteria. Digoxin and talinolol are suitable in vivo probe drugs for intestinal P-gp under the precondition, that they are used as tools in carefully designed pharmacokinetic studies with adequate biometrically planning of the sample size and that several limitations are considered in interpreting and discussion of the study results.

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“…Milk fat can concentrate lipid‐soluble drugs, causing the total amount of drug in milk to increase. For highly lipids‐soluble drugs such as diazepam and phenytoin, a large percentage of the total amount of drug in breastmilk is found in milk fat . Nevertheless, because the volume of fat in milk is small compared with the total volume of milk, the net effect of lipid partitioning on most drugs is relatively small.…”

Section: Excretion Of Drugs Into Milkmentioning

confidence: 99%

Modeling drug passage into human milk

Anderson

Sauberan

2016

Clin Pharma and Therapeutics

109

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Breastfeeding has positive health consequences for both the breastfed infant and the nursing mother.(1,2) Although information on drug use during lactation is available through sites such as LactMed,(3) available information is often incomplete. Unlike pregnancy, in which large numbers of pregnant women need to be studied to assure safety, measurement of drug concentrations in breastmilk in a relatively few subjects can provide valuable information to assess drug safety. This article reviews methods of measuring and predicting drug passage into breastmilk.

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Relationship between Human Milk Lipid-Ultrafiltrate and Octanol-Water Partition Coefficients

Cited by 47 publications

References 16 publications

Retraction: Acute Myelogenous Leukemia Following Mitoxantrone Treatment for Multiple Sclerosis

Retraction: Acute Myelogenous Leukemia Following Mitoxantrone Treatment for Multiple Sclerosis

In Vivo Probes of Drug Transport: Commonly Used Probe Drugs to Assess Function of Intestinal P-glycoprotein (ABCB1) in Humans

Modeling drug passage into human milk

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