Establishing Quality Assurance Criteria for Serial Dilution Operations on Liquid-Handling Equipment

Matching the power of high throughput screening to the chemical diversity of natural products

“…For example, variations in solvents for sample solubilization, 66 dilution schemes, 66,67 order of reagent addition, 68 and methods for delivery of samples to assay plates 69 can often resolve sample-related issues, independent of the source of the samples. Variations in sample preparation procedures, including alternative solvents and use of carrier macromolecules for stabilization have been successfully applied to problems arising in the preparation of natural product extracts for HTS.…”

“…Variations in sample preparation procedures, including alternative solvents and use of carrier macromolecules for stabilization have been successfully applied to problems arising in the preparation of natural product extracts for HTS. 62 Application of standard sample management techniques 70 as well as proper use, maintenance, and calibration of liquid handling equipment 67 can often forestall sample handling problems. Sample storage and management are further discussed below as focused on natural product extracts.…”

Intelligent Automation Platform for Bioprocess Development

“…Broadly speaking, the quality of biochemical experiment results depends on two factors: 1) the assay variability, and 2) the product concentration (Hentz & Knaide 2014). In turn, the sample concentration in the assay depends on many factors, such as initial concentration of the stock solution, sample storage, handling throughout the process, solubility and stability of the sample in medium buffer, and pipetting accuracy and dilution scheme (Popa-Burke et al 2009). …”

“…MAD (median absolute deviation) is considered better method for outlier detection (Popa-Burke et al 2009). MAD is a measure of statistical dispersion, and it is more resilient to outliers in a data set than the standard deviation.…”

“…Normally, observation farther than 4.5MAD from the median are marked to be outlier (Popa-Burke et al 2009). Since the standard deviation of a normal distribution is 1.5 times the MAD (Pereira & Williams 2007), the cutoff is three standard deviations from the mean, where only 0.3% population will lie here for a normal distribution.…”