Analysis of Imprecision in Incurred Sample Reanalysis for Small Molecules

Subramaniam, Sriram; Patel, Devvrat T.; Davit, Barbara M.; Conner, Dale P.

doi:10.1208/s12248-014-9689-1

Cited by 8 publications

(8 citation statements)

References 14 publications

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“…Unlike the regulated bioanalysis requirement for assessing ISR after completion of every study when the drug enters drug development (Fluhler et al, ; Hoffman, ; Subramaniam, Patel, Davit, & Conner, ; Timmerman et al, ), we wanted to check the feasibility of a system that examines ISR on a periodic basis (i.e. half‐yearly) without over‐burdening the throughput analysis and rapid data turnaround time, which are mandatory at the drug discovery stage.…”

Section: Methodsmentioning

confidence: 99%

Incurred sample reanalysis in drug discovery bioanalysis

Giri

Patel

Joshi

et al. 2018

Biomedical Chromatography

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Bioanalysis plays a key role during the drug discovery process to generate the pharmacokinetic data to facilitate unbiased evaluation of leads, optimized leads and drug candidates. Such pharmacokinetic data are used to enable key decisions in the drug discovery process. The aim of the work is to put forward a new strategy of performing the incurred sample reanalysis for select small molecule novel chemical entities at different stages of drug discovery prior to candidate selection.Three discovery programs representing hits, leads and optimized lead candidates were selected for the incurred sample reanalysis (ISR) analysis. From each discovery program, two novel chemical entities were selected for the ISR analysis. The time points considered for ISR generally varied among the programs; however, samples coinciding with drug absorption, distribution and elimination were considered in the ISR assessment. With the exception of a single ISR value that gave a high deviation (about 63%), the observed ISR values supported the discovery bioanalytical assays. While the individual bioanalytical laboratory can draw an algorithm for selecting novel chemical entities and fixing the acceptance criteria for the ISR data, it is proposed that the percentage difference between ISR vs. original concentration for 67% of the repeat samples is contained within ±30% for discovery bioanalysis.

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Section: Methodsmentioning

confidence: 99%

Incurred sample reanalysis in drug discovery bioanalysis

Giri

Patel

Joshi

et al. 2018

Biomedical Chromatography

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“…The calculations using the hypergeometric distribution are complementary to the published simulations (10,18,19), but they have significant advantages. The novel model uses %ISR to include both random (imprecision) and systematic (bias, metabolite conversion) errors.…”

Section: Discussionmentioning

confidence: 99%

“…The Global Bioanalysis Consortium suggested, in turn, to reanalyze the fixed ratio of 5% of clinical samples that is equal to the ratio of quality control (QC) samples in a bioanalytical batch (9). More recently, Subraminiam et al presented a comprehensive ISR simulation for small molecules using various combinations of precision and bias (10). It revealed that if 20 ISRs are analyzed and the method’s precision up to 15% is combined with the bias not exceeding 10%, then over 0.85 of the studies pass the ISR test.…”

Section: Introductionmentioning

confidence: 99%

“…They also suggest that for reproducible methods, only 40–50 samples are enough to meet the ISR passing rate over 99%. Yet, some of the assumptions seem questionable, like no bias (18,19) or a narrow concentration range (10,19). Moreover, we have recently suggested that the number of ISRs recommended by FDA and EMA (5,7) does not seem to be well matched with the acceptance criteria (12).…”

Section: Introductionmentioning

confidence: 99%

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Incurred Sample Reanalysis: Time to Change the Sample Size Calculation?

Rudzki

Biecek

Kaza

2019

AAPS J

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Reliable results of pharmacokinetic and toxicokinetic studies are vital for correct decision making during drug discovery and development. Thus, ensuring high quality of bioanalytical methods is of critical importance. Incurred sample reanalysis (ISR)—one of the tools used to validate a method—is included in the bioanalytical regulatory recommendations. The methodology of this test is well established, but the estimation of the sample size is still commented on and contested. We have applied the hypergeometric distribution to evaluate ISR test passing rates in different clinical study sizes. We have tested both fixed rates of the clinical samples—as currently recommended by FDA and EMA—and a fixed number of ISRs. Our study revealed that the passing rate using the current sample size calculation is related to the clinical study size . However, the passing rate is much less dependent on the clinical study size when a fixed number of ISRs is used. Thus, we suggest using a fixed number of ISRs, e.g., 30 samples, for all studies. We found the hypergeometric distribution to be an adequate model for the assessment of similarities in original and repeated data. This model may be further used to optimize the sample size needed for the ISR test as well as to bridge data from different methods. This paper provides a basis to re-consider current ISR recommendations and implement a more statistically rationalized and risk-controlled approach.

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“…Incurred sample reanalysis (ISR) was performed as a supplement to verify the reproducibility of the bioanalytical method . The ISR was conducted by remeasurement of subsamples; the acceptance criteria was that the difference between initial and reanalyzed concentrations when normalized to their means should be within 20.0% for at least two thirds of the samples.…”

Section: Methodsmentioning

confidence: 99%

Determination of DP‐VPA and its active metabolite, VPA, in human plasma, urine, and feces by UPLC–MS/MS: A clinical pharmacokinetics and excretion study

Zhan

Fan

et al. 2019

Drug Testing and Analysis

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DP‐VPA is a phospholipid prodrug of valproic acid (VPA) that is developed as a potential treatment for epilepsy. To characterize the pharmacokinetics and excretion of DP‐VPA, four reliable ultra‐performance liquid chromatography–tandem mass spectrometry (UPLC–MS/MS) methods were validated for quantitation of DP‐VPA and its metabolite, VPA, in human plasma, urine, and feces. Protein precipitation and solid‐phase extraction (SPE) were used for extraction of C16, C18 homologs of DP‐VPA and VPA, respectively, from plasma. Urine and fecal homogenate involving the three analytes were efficiently prepared by methanol precipitation. The determinations of C16 DP‐VPA, C18 DP‐VPA, and VPA were performed using the positive multiple reaction monitoring (MRM) mode and the negative single ion monitoring (SIM) mode, respectively. The analytes were separated using gradient elution on C8 or phenyl column. Satisfactory results pertaining to selectivity, linearity, matrix effect, accuracy and precision, recovery, stability, dilution integrity, carryover, and incurred sample analysis (ISR) were obtained. The calibration ranges in human plasma were as follows: 0.00200–1.00 μg/mL for C16 DP‐VPA, 0.0100–5.00 μg/mL for C18 DP‐VPA, and 0.0500–20.0 μg/mL for VPA. The linear ranges in urine and fecal homogenate were 0.00500–2.00 μg/mL and 0.00200–0.800 μg/mL for C16 DP‐VPA, 0.00500–2.00 μg/mL and 0.0100–4.00 μg/mL for C18 DP‐VPA, and 0.200–80.0 μg/mL for VPA, respectively. The intra‐ and inter‐batch coefficients of variation in three matrices ranged from 1.7% to 12.4% while the accuracy values ranged from 85.4% to 111.7%. The developed methods were successfully applied to determine pharmacokinetics of DP‐VPA tablet after a single oral dose of 1200 mg in 12 healthy Chinese subjects under fed condition.

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Analysis of Imprecision in Incurred Sample Reanalysis for Small Molecules

Cited by 8 publications

References 14 publications

Incurred sample reanalysis in drug discovery bioanalysis

Incurred sample reanalysis in drug discovery bioanalysis

Incurred Sample Reanalysis: Time to Change the Sample Size Calculation?

Determination of DP‐VPA and its active metabolite, VPA, in human plasma, urine, and feces by UPLC–MS/MS: A clinical pharmacokinetics and excretion study

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