Drug mixtures and infusion technology. MasterChef or Hell’s Kitchen?

AbstractMixtures of drugs often have greater therapeutic value than any of their constituent drugs alone, and such combination therapies are widely used to treat diseases such as cancer, malaria, and viral infections. However, developing useful drug mixtures is challenging due to complex interactions between drugs. Natural substances can be fruitful sources of useful drug mixtures because secondary metabolites produced by living organisms do not often act in isolation in vivo. In order to facilitate the study of interactions within natural substances, a new analytical method to quantify interactions using data generated in the process of bioassay-guided fractionation is presented here: the extract fractional inhibitory concentration index (EFICI). The EFICI method uses the framework of Loewe additivity to calculate fractional inhibitory concentration values by which interactions can be determined for any combination of fractions that make up a parent extract. The EFICI method was applied to data on the bioassay-guided fractionation of Lechea mucronata and Schinus terebinthifolia for growth inhibition of the pathogenic bacterium Acinetobacter baumannii. The L. mucronata extract contained synergistic interactions (EFICI = 0.4181) and the S. terebinthifolia extract was non-interactive overall (EFICI = 0.9129). Quantifying interactions in the bioassay-guided fractionation of natural substances does not require additional experiments and can be useful to guide the experimental process and to support the development of standardized extracts as botanical drugs.

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Simple Method for Determination of Glycine and Niacin in Drug Mixtures

Journal of AOAC INTERNATIONAL ◽

10.1093/jaoac/51.1.11 ◽

1968 ◽

Vol 51 (1) ◽

pp. 11-14

Author(s):

Keith L Egli ◽

Anthony Romano

Keyword(s):

Thin Layer ◽

Thin Layer Chromatography ◽

Ultraviolet Absorption ◽

Simple Method ◽

Drug Mixtures ◽

Layer Chromatography

Abstract A method, based on the formol titration of glycine and the ultraviolet absorption of niacin, has been developed for the determination of these compounds in drug mixtures. Neither compound requires isolation for the determination. Glycine and niacin are identified by thin layer chromatography

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Evaluation of Capillary Gas Chromatography for Multicomponent Drug Analysis

Journal of AOAC INTERNATIONAL ◽

10.1093/jaoac/69.5.811 ◽

1986 ◽

Vol 69 (5) ◽

pp. 811-813

Author(s):

Don W Thompson

Keyword(s):

Gas Chromatography ◽

Capillary Gas Chromatography ◽

Drug Analysis ◽

Fused Silica ◽

Pharmacological Activities ◽

Over The Counter ◽

Silica Column ◽

Drug Mixtures ◽

Bonded Phase ◽

Glass Column

Abstract Capillary gas chromatography is evaluated for multicomponent drug analysis. A 0.32 mm id × 30 m fused silica column and a 0.75 mm id × 30 m borosilicate glass column (both with OV-1 bonded phase) are investigated. Retention times (relative to caffeine) are presented for 39 drug components representing a variety of chemical classes and pharmacological activities. Reproducibility data are presented for both isothermal and programmed temperature runs on selected drug mixtures. Recovery data are provided for 2 multicomponent drug mixtures prepared to approximate over-the-counter antihistaminic and antitussive preparations.

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Discrimination of pentobarbital doses and drug mixtures under fixed-ratio and fixed-interval reinforcement schedules

Behavioural Pharmacology ◽

10.1097/00008877-200105000-00005 ◽

2001 ◽

Vol 12 (3) ◽

pp. 195-208 ◽

Cited By ~ 7

Author(s):

D.E. McMillan ◽

W.C. Hardwick ◽

Mi Li

Keyword(s):

Fixed Ratio ◽

Fixed Interval ◽

Reinforcement Schedules ◽

Drug Mixtures

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Drug-excipient and drug-drug mixtures: a pathway for the production of co-amorphous entities

Annals of Medicine ◽

10.1080/07853890.2018.1561802 ◽

2019 ◽

Vol 51 (sup1) ◽

pp. 87-87

Author(s):

Nuno F. da Costa ◽

João F. Pinto ◽

Ana I. Fernandes

Keyword(s):

Drug Mixtures

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Noninvasive, Quantitative Analysis of Drug Mixtures in Containers Using Spatially Offset Raman Spectroscopy (SORS) and Multivariate Statistical Analysis

Applied Spectroscopy ◽

10.1366/11-06554 ◽

2012 ◽

Vol 66 (5) ◽

pp. 530-537 ◽

Cited By ~ 17

Author(s):

William J. Olds ◽

Shankaran Sundarajoo ◽

Mark Selby ◽

Biju Cletus ◽

Peter M. Fredericks ◽

...

Keyword(s):

Raman Spectroscopy ◽

Quantitative Analysis ◽

Pharmaceutical Products ◽

Counterfeit Drugs ◽

Multivariate Statistical ◽

Plastic Container ◽

Phenylephrine Hydrochloride ◽

Drug Mixtures ◽

Target Drug ◽

Drug Concentrations

In this paper, spatially offset Raman spectroscopy (SORS) is demonstrated for noninvasively investigating the composition of drug mixtures inside an opaque plastic container. The mixtures consisted of three components including a target drug (acetaminophen or phenylephrine hydrochloride) and two diluents (glucose and caffeine). The target drug concentrations ranged from 5% to 100%. After conducting SORS analysis to ascertain the Raman spectra of the concealed mixtures, principal component analysis (PCA) was performed on the SORS spectra to reveal trends within the data. Partial least squares (PLS) regression was used to construct models that predicted the concentration of each target drug, in the presence of the other two diluents. The PLS models were able to predict the concentration of acetaminophen in the validation samples with a root-mean-square error of prediction (RMSEP) of 3.8% and the concentration of phenylephrine hydrochloride with an RMSEP of 4.6%. This work demonstrates the potential of SORS, used in conjunction with multivariate statistical techniques, to perform noninvasive, quantitative analysis on mixtures inside opaque containers. This has applications for pharmaceutical analysis, such as monitoring the degradation of pharmaceutical products on the shelf, in forensic investigations of counterfeit drugs, and for the analysis of illicit drug mixtures which may contain multiple components.

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