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In Silico Predictions of the Gastrointestinal Uptake of Macrocycles in Man Using Conformal Prediction Methodology

Fagerholm, Urban (author)
Prosilico AB, Lannavagen 7, SE-14145 Huddinge, Sweden.
Hellberg, Sven (author)
Prosilico AB, Lannavagen 7, SE-14145 Huddinge, Sweden.
Alvarsson, Jonathan, 1981- (author)
Uppsala universitet,Institutionen för farmaceutisk biovetenskap,Science for Life Laboratory, SciLifeLab
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Spjuth, Ola, Professor, 1977- (author)
Uppsala universitet,Institutionen för farmaceutisk biovetenskap,Science for Life Laboratory, SciLifeLab,Prosilico AB, Lannavagen 7, SE-14145 Huddinge, Sweden.
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Prosilico AB, Lannavagen 7, SE-14145 Huddinge, Sweden Institutionen för farmaceutisk biovetenskap (creator_code:org_t)
Elsevier, 2022
2022
English.
In: Journal of Pharmaceutical Sciences. - : Elsevier. - 0022-3549 .- 1520-6017. ; 111:9, s. 2614-2619
  • Journal article (peer-reviewed)
Abstract Subject headings
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  • The gastrointestinal uptake of macrocyclic compounds is not fully understood. Here we applied our previously validated integrated system based on machine learning and conformal prediction to predict the passive fraction absorbed (f(a)), maximum fraction dissolved (f(diss)), substrate specificities for major efflux transporters and total fraction absorbed (f(a,tot)) for a selected set of designed macrocyclic compounds (n = 37; MW 407-889 g/mol) and macrocyclic drugs (n = 16; MW 734-1203 g/mole) in vivo in man. Major aims were to increase the understanding of oral absorption of macrocycles and further validate our methodology. We predicted designed macrocycles to have high f(a )and low to high f(diss) and f(a,tot, )and average estimates were higher than for the larger macrocyclic drugs. With few exceptions, compounds were predicted to be effluxed and well absorbed. A 2-fold median prediction error for f(a,tot )was achieved for macrocycles (validation set). Advantages with our methodology include that it enables predictions for macrocycles with low permeability, Caco-2 recovery and solubility (BCS IV), and provides prediction intervals and guides optimization of absorption. The understanding of oral absorption of macrocycles was increased and the methodology was validated for prediction of the uptake of macrocycles in man.(C) 2022 American Pharmacists Association. Published by Elsevier Inc. All rights reserved.

Subject headings

MEDICIN OCH HÄLSOVETENSKAP  -- Medicinska och farmaceutiska grundvetenskaper -- Läkemedelskemi (hsv//swe)
MEDICAL AND HEALTH SCIENCES  -- Basic Medicine -- Medicinal Chemistry (hsv//eng)

Keyword

Absorption
Machine learning
Permeability
Solubility
Dissolution
PBPK

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Fagerholm, Urban
Hellberg, Sven
Alvarsson, Jonat ...
Spjuth, Ola, Pro ...
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