Ambiguous Automation

A pharmaceutical specialty is produced in three dosage strengths (major component A) A and a second component B are controlled by HPLC for batch release purposes. It is decided to replace the manual injection of the sample solution by an automatic one. It is expected the means will remain the same but the standard deviations will be smaller for the automatic injection. Cross-validation of the methods is effected by running both methods on each of 10 samples. The mean and the standard deviation for each series of 10 measurements is given in Table 4.19. 

The residual SD decreased markedly in three cases (7.03 — 5.56, 5.66 — 2.68, 1.59 — 0.75), remained about the same in the other cases this shows that automation had the desired effect, only it was overshadowed by the earlier point 1. The average decrease in Vres is 42%. 

Observation 1 is an illusion due to the fact that the above numbers measure the overall spread in one dimension (vertical or horizontal), and do not take into account the correlation between the results A and B that is very much in evidence in the right side of Fig. 4.22 (automatic injection), also see Fig. 1.23. The variability can be measured in five different ways (see Table 4.20)  

From the preceding discussion, it can be gathered that the automatic injection should eventually lead to more reproducible results (the residual standard deviation decreases by about 20%), but only if the spread along the 

5 along the diagonal Sk coordinate - mean/ymean Sx Sy Sinjection 

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With mostly unambiguous data, this protocol has been successfully used for proteins with up to 160 residues [62]. Although virtually all structures converge to the correct fold for small proteins, we observe that approximately one-third of the structures are misfolded for larger proteins, or for low data density, or many ambiguities (see, e.g.. Ref. 63). We have also used this protocol for most structure calculations with the automated NOE assignment method ARIA discussed in the next section. 

Figure 6 Steps in automated assignment. (1) Select the lowest energy structures from iteration / — 1 that are used to interpret the spectra. (2) For each peak, list all possible assignments compatible with the resonances within a frequency mnge. (3) Extract a distance for each assignment possibility from the ensemble of structures. (4) Use the distances to assign ambiguous NOEs. (5) Calibrate the peak volumes to obtain distance restraints. (6) Calculate structures based on the new restraints.

These considerable solvent-dependent shifts demonstrate that for molecules with such pronounced conformational ambiguity, the equilibration of conformations has to be taken into account in the calculation of thermodynamic phase-equilibrium data. In order to enable a consistent treatment, we have implemented an automated conformation equilibration scheme in COSMO therm. A compound X can be represented by a set of COSMO-files for the conformers, and a multiplicity ojx(i) can be assigned to each con-former based on geometrical degeneration aspects. Then the population of a conformer, i, in a solvent S is calculated as... 

Automated Edman degradation was performed on. 200 pmol of purified Hez-PBAN using the pulsed-liquid sequencer. Data were obtained from 33 cycles (Table I, run 3). However, the residues at positions 23 and 32 could not be ambiguously assigned. A second attempt on the same instrument using sample purified from the PBAN II zone confirmed the earlier sequence and established the residues at positions 23 and 32 (Table I, run 4). 

The coordination of suppliers is vital, and, to this end, a Validation Master Plan is often produced, referencing a number of Validation Plans for each element of the automated medical device. Suppliers should be encouraged to produce their own Quality Plans in response to the Validation Plan for their portion of the system so that any inconsistencies and ambiguities can be identified and corrective actions instituted before change becomes too inconvenient and expensive. 

Linge IP, O Donoghue SI, Nilges M. Automated assignment of ambiguous nuclear overhauser effects with ARIA. Methods Enzymol. 2001 339 71-90. 

The expert, a senior research chemist for example, defines a problem domain and injects some of his knowledge about that particular area into the KEY system. KEY analyzes this knowledge and provides the expert with automated techniques to isolate and eliminate inconsistencies and ambiguities. Once these are removed, the knowledge is converted into rules. These rules are the power that drives the inference engine. The result of... 

Nilges M (1995) Calculation of protein structures with ambiguous distance restraints. Automated assignment of ambiguous NOE crosspeaks and disulphide connectivities. J Mol Biol 245(5) 645-660... 

Leplat suggests that accidents are most likely in overlap areas or in boundary areas or where two or more controllers (human or automated) control the same process or processes with common boundaries (figure 4.9) [112]. In both boundary and overlap areas, the potential exists for ambiguity and for conflicts among independent decisions. 

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