Novel methodology to perform incurred sample reanalysis on dried blood spot cards: Experimental data using darolutamide and filgotinib.
Vinay KiranAbhishek DixitBhavesh Babulal GabaniNuggehally R SrinivasRamesh MullangiPublished in: Biomedical chromatography : BMC (2020)
Different options on performing incurred sample reanalysis (ISR) on dried blood spot (DBS) cards were investigated using drugs belonging to various therapeutic areas: (a) darolutamide (to treat prostate cancer) and (b) filgotinib (to treat rheumatoid arthritis). The proposed novel methodology included the generation of half-DBS and quarter-DBS discs after initial blood collection using the full-DBS discs. Accordingly, blood collection via DBS was performed in male BALB/c mice following intravenous and oral dosing of darolutamide; in male Sprague Dawley rats following intravenous and oral dosing of filgotinib. The ISR data generated from the full-DBS disc, half-DBS disc and quarter-DBS disc were compared for the assessment of the proposed methodology. Quantification of darolutamide and filgotinib was accomplished using liquid chromatography-electrospray ionization/tandem mass spectrometry methods. Darolutamide and filgotinib ISR samples, which were collected and prepared using full-, half- and quarter-DBS discs, met the acceptance criteria for ISR analysis. In conclusion, this is the first report showing a viable tool for the performance of ISR on DBS cards. The use of quarter- or half-DBS discs would aid in not only ISR but also in long-term storage experiments of analytes because it would avoid the need for additional blood sampling in patients.
Keyphrases
- deep brain stimulation
- prostate cancer
- liquid chromatography
- tandem mass spectrometry
- rheumatoid arthritis
- end stage renal disease
- mass spectrometry
- ultra high performance liquid chromatography
- big data
- chronic kidney disease
- radical prostatectomy
- machine learning
- electronic health record
- metabolic syndrome
- simultaneous determination
- skeletal muscle
- artificial intelligence
- tyrosine kinase
- peritoneal dialysis
- deep learning
- ankylosing spondylitis
- interstitial lung disease
- systemic sclerosis
- gas chromatography