Workflow validation

The ultimate goal of all scientists is to analyze their data thoroughly until they are sure that it is valid and to then analyze it in a more global context and discuss it with their colleagues. This workflow requires enterprise level IT tools that can effectively compare and correlate multiple HTS campaigns that generated millions of results from hundreds of thousands of compounds, recognize and chart trends and hierarchies of association and help the scientist visualize them, annotate them, and render the visualizations in media that can be used to share that vision with other members of the team. 

In our laboratories, a cycle time of 90 sec can be achieved with a dilution factor of 1 25 for a given sample concentration, allowing the purity and identity control of two and a half 384-well microtiter plates per day. The online dilution eliminated an external step in the workflow and reduced the risks of decomposition of samples in the solvent mixture (weakly acidic aqueous solvent) required for analysis. Mao et al.23 described an example in which parallel sample preparation reduced steps in the workflow. They described a 2-min cycle time for the analysis of nefazodone and its metabolites for pharmacokinetic studies. The cycle time included complete solid phase extraction of neat samples, chromatographic separation, and LC/MS/MS analysis. The method was fully validated and proved rugged for high-throughput analysis of more than 5000 human plasma samples. Many papers published about this topic describe different methods of sample preparation. Hyotylainen24 has written a recent review. 

Bigure 16.5 summarizes our approach to using validated QSAR models for virtual screening as applied to the anticonvulsant dataset. It presents a practical example of the drug discovery workflow that can be generalized for any dataset in which sufficient data to develop reliable QSAR models is available. 

Fig. 16.5 Computer-aided drug discovery workflow based on combination of QSAR modeling and consensus database mining as applied to the discovery of novel anticonvulsants [10]. The workflow emphasizes the importance of model validation and applicability domain in ensuring high hit rates as a result of database mining with predictive QSAR models.

A practical solution to this problem, called GLARE (Global Library Assessment of REagents) (4), has been developed and validated in our laboratories and is explained in this chapter. We will focus on a specific chemical combinatorial library to illustrate the workflow and the use of the software. 

Symyx entered this competition in 1997 in collaboration with Hoechst with the goal of creating and validating primary and secondary synthesis and screening technologies and the use of this workflow to broadly explore mixed metal oxide compositions so as to discover and optimize new hits . The initial goal was a 10-fold increase in the space-time yield relative to the state-of-the-art MoVNb system for the ethane oxidative dehydrogenation reaction to ethylene. 

Fig. 1.4 compares, in topological format, the space-time yield versus composition for the data presented in the 1978 Union Carbide publication and the activity rankings observed in the SMS in an experiment that took less than 4 h, most of which was unattended. The correlation is remarkable. The primary synthesis and screening components of the workflow were thus validated. Hif criteria were established that involved ranking the yield of the reaction over the various catalysts (the activity figure of merit multiplied by selectivity). The hif criteria performance bar increased as the discovery program evolved and improved systems were discovered. 

The 48-channel MCFB reactor and the catalyst synthesis workflow components were similarly validated in experiments where bulk samples were prepared in library format, screened in the array format, and the data compared with known examples. This part of the workflow was used for initial hit validation and to opti-... 

The state-of-the-art catalyst system is a Mo-V-Nb-Te mixed oxide [52], This catalyst is quite sensitive to its synthesis and process parameters and the automated catalyst synthesis tools described above were capable of synthesizing these and other challenging mixed metal oxides successfully. The workflow was validated by synthesizing a region of the known Mo-V-Nb-Te catalyst system phase space in the primary scale and secondary scale (Fig. 3.19a and b). Very good agreement between primary, secondary, and literature optima were obtained. One of the pri-... 

Structural and compositional characterization of individual elements of a combinatorial library can be important for the initial validation of a particular combinatorial synthesis method. Many earlier reports on combinatorial synthesis and screening of electrocatalysts fall short of reporting the complete structural and compositional characterization of individual library elements of interest. The workflow described here includes catalyst characterization before and after screening, thereby establishing an activity-composition-structure-stability relationship for electrocatalysts. This can be relevant in light of the extreme conditions present in a conventional fuel cell environment. 

The primary and secondary electrochemical workflows presented above have been successfully validated and applied to the development of new compositions for fuel cell catalysts, specifically to the search for more active ternary and higher-order catalyst compositions for the electrochemical oxidation of methanol in acidic solutions [18, 19]. Some results of this study are now illustrated. 

Key practices Processes essential for computer validation that consists of tools, workflow, and people (PDA). 

FIGURE 1 Example of a gel-free-oriented proteomics nano-LC/MS-MS workflow in which bacterial culture proteins digested to tryptic peptides are separated via LC and peptides subsequently analyzed by mass spectrometry. In the process, the spectrometer rapidly cycles every few seconds and examines a size window in which peptide-derived MSI ions are analyzed to define MS/MS (MS2) spectra. The MS/MS (MS2) spectrum generated for each peptide then enters a bioinformatic pipeline for sequence identification, statistical validation, and quantification. 

The subsequent downstream processing section, which includes visualization of quantified proteins, statistical validation of differences in treatments or samples, and biological interpretation, is much less defined in terms of work-flow regimens and is discussed toward the end of this chapter. In the succeeding text, various relevant aspects of proteomic workflows that impinge on the data obtained from proteomic analysis of prokaryotes assuming that a gel-free approach is used are discussed. 

Pyrococcus furiosus Thermophile Multimethod, multilab Workflow and quantification validation (218)... 

To illustrate the power of validated QSAR models as virtual sereening tools we diseuss the examples of studies that resulted in experimentally eonfirmed hits. Sueh studies eould only be performed if there is sufficient data available for a series of tested compounds such that robust validated models could be developing using the workflow described in Figure 10.1. 

---