Recent Applications of Accelerated Structure Analysis Protocols

Edward H. Kerns^l*, Kevin J. Volk², Mark E. Hail³, Jeffrey L. Whitney², Robyn A. Rourick², Steven E. Klohr² and Mike S. Leel

Bristol-Myers Squibb Pharmaceutical Research Institute
(1) P.O. Box 191, New Brunswick, NJ 08903
(2) P.0. Box 4000, Princeton, NJ 08543
(3) P.O. Box 5100, Wallingford, CT 06492

Note: This paper was originally presented at The 1996 International Symposia on Laboratory Automation and Robotics (ISLAR96)

http://www.netsci.org/Science/LIMS/feature01.html

ABSTRACT

Proactive strategies utilizing LC/MS techniques have been developed to facilitate accelerated activities in pharmaceutical research, development and manufacturing. These have been successfully applied to routine analyses and benchmarked for productivity increases of 3 to 18 fold. These strategies apply universally throughout pharmaceutical activities and provide increased levels of critical information than has been previously available.

INTRODUCTION

The pharmaceutical industry continues to undergo unprecedented change. Advanced technologies, such as gene sequencing, high throughput screening and combinatorial chemistry accelerate therapeutic target identification and active chemotype identification/refinement. Organizational initiatives, such as parallel operations and early initiation of projects, have dramatically reduced the time line of product research and development. Emphasis is focused on enhancement of productivity and shortened time lines.

In this environment, analytical measurements provide critical information for pharmaceutical industry activities throughout the discovery -- development -- manufacturing continuum. Thus, we have placed emphasis on the development and implementation of strategies which provide increased levels of analytical information in reduced time periods.

MASS SPECTROMETRY TECHNOLOGY

Mass spectrometry techniques provide analytical opportunities consistent with current trends. Mass spectrometry has many advantageous characteristics: high sensitivity, selectivity, speed, and "universal" application. Liquid chromatography/mass spectrometry (LC/MS) instrumentation couples high performance liquid chromatography (HFLC) with tandem mass spectrometry (MS/MS) via the electrospray interface, providing synergies from a widely utilized separation technique detailed spectroscopic information for structure identification. The traditional structure analysis protocols involving scaleup, extraction, fractionation and individual fraction spectroscopic analysis may be performed more rapidly within the LC/MS instrument. Integration of automated LC/MS into existing structure analysis protocols facilitates accelerated production of critical structural information.

Figure 1
Transfer of Bench-Scale Experimental Steps to Instrumental Format

ANALYTICAL STRATEGY DEVELOPMENT

We have applied LC/MS technology in proactive analytical methods. This approach has been benchmarked with favorable levels of structure analysis productivity enhancement. Therefore, we utilize LC/MS methods for primary analysis in many of the analytical tasks of exploration, research, development and manufacturing.

Our previous structure analysis strategies relied upon multiple spectroscopic and physical techniques performed sequentially (i.e., elemental analysis, MS, IR and NMR). With the multiplication of sample generation by combinatorial chemistry techniques our new analytical strategy focuses on MW as the critical element of confirmation for synthetic compounds. This strategy rapidly provides sufficient information for a project to continue without delay. More detailed studies are conducted at a later time if the candidate compound proves to have pharmaceutical activity. In the same manner, other analytical strategies for support of all phases of pharmaceutical activities have been implemented for productivity enhancement. Some of these are described below.

LC/MS is often considered a resource-intensive method. Frequently, this is because every LC/MS analysis is viewed as a "custom" analysis, due to the variability of HPLC conditions (e.g., column, mobile phase, flow rate, gradient) employed for different projects. The process of changing from one condition to another and re-testing the system can require as much time as the actual LC/MS analysis. We have instituted the use of standard methods. With this approach over 80% of our sample analysis projects can be conducted with one method. As a result, productivity is greatly increased. Standard methods also facilitate automation of LC/MS for overnight/unattended analysis. Productivity increases of 3-5 fold have been benchmarked.

Our methods are typically locked-in early in the product development cycle. Early method lock-in permits the reduction of method development and validation steps. Furthermore, it permits the comparison of analytical information obtained over a long period, as opposed to the uncertainty associated with comparing information collected under different conditions.

LC/MS information is assembled into structure profile libraries (SPL), which provide a concise reference for each drug candidate. The SPL allows the accelerated identification of impurities, degradants and metabolites in samples analyzed throughout the drug's lifetime.

SPLs are proactively initiated early in a candidate's lifetime, using predictive models, before critical samples are encountered,. The candidate drug is exposed to various environments encountered in discovery, development and manufacturing processes to produce degradants, impurities, and metabolites of the drug. These are identified and included in the candidate's SPL.

Our structure elucidation strategy for unknown analogs of a candidate drug is based on using the drug molecule for template analysis. This approach is based on the premise that degradants, impurities and metabolites retain some of the substructures of the parent drug and, thus, produce the specific MS/MS product ions and neutral losses associated with those substructures. This strategy permits the rapid identification of analog structures without requiring time consuming steps of traditional structure analysis strategies involving scale-up, extraction, fractionation and spectroscopic analysis of individual fractions.

Applications of these strategies are discussed in the following examples drawn from pharmaceutical R&D activities.

APPLICATION OF LC/MS ANALYTICAL STRATEGIES

Metabolite Profiling

The disposition of a drug in a living animal is a key determinant of its efficacy. When metabolism information is available at an early stage in R&D, new candidate drug molecules may be designed to block major sites of metabolic degradation. Previously, metabolite profiles relied on analytical protocols involving radio-labeled drugs, scale-up, extraction, fractionation and individual component spectroscopic analysis. However, LC/MS protocols allow for the accelerated profiling of metabolites in trace mixtures. As a result, metabolism guided structure modification for the optimization of drug candidates is facilitated.

Our high throughput metabolite profiling strategy is based on automated LC/MS techniques. Sample preparation has been simplified to the addition of acetonitrile to small volumes of bile, urine or liver S9 incubation samples (to precipitate protein and salts), followed by centrifugation. The supernatant is placed into a 200 µL vial and placed in queue in an HP1090M autosampler. We utilize a standard LC/MS method involving the gradient reverse phase elution of a Zorbax C18 column over 15 min. An on-line diode array detector provides a LC/UV chromatogram which is complementary to the electrospray LC/MS chromatogram. The LC/LTV and LC/MS chromatograms are utilized to tabulate the mixture components and to identify their MWs. MS/MS product ion spectra are subsequently obtained for each metabolite. The structures of the metabolites are interpreted based on the template drug structure.

As an example of this protocol, metabolites of buspirone, a well known central nervous system drug, have been profiled. Buspirone metabolism has been previously characterized, making buspirone an ideal model. The buspirone metabolite SPL resulting from this analysis is shown in Table 1. This analysis provided evidence for nearly all of the buspirone metabolites which had been previously reported, as well as several metabolites which had not been previously known.

Table 1
Buspirone Metabolite Structure Profile Library

Buspirone

PROPOSED STRUCTURE	RRT^a	MH^+b	R₁	R₂	R₃
Hydroxy buspirone glucuronide	0.14	594	+OH	+OH	+Glucuronyl
Hydroxy buspirone glucuronide	0.30	594	+OH	+OH	+Glucuronyl
Hydroxy buspirone glucuronide	0.35	594	+OH	+OH	+Glucuronyl
Hydroxy methoxy buspirone glucuronide	0.36	624	+OH, +OCH3	+OH	+Glucuronyl
Hydroxy methoxy buspirone glucuronide	0.38	624	+OH, +CCH3	+OH	+Glucuronyl
Hydroxy buspirone glucuronide	0.38	594	+OH	+OH	+Glucuronyl
I-Pyrimidinyl piperazine	0.42	165	U	N
Buspirone Glucuronide	0.44	571	+OH +Glucuronyl
Dihydroxy buspirone	0.45	418	U	+2(OH)
Methoxy buspirone glucuronide	0.46	608	+OH, +CCH3		+Glucuronyl
Dihydroxy buspirone	0.48	418	U	+2(OH)
Dihydroxy buspirone	0.48	418	+OH	+OH
Despyrimidinyl piperazine buspirone	0.50	254	N	U	-Pyrimidinyl piperazine, +=O, +OH
Dihydroxy methoxy buspirone	0.51	448	+OH, +CCH3	+OH
Hydroxy buspirone	0.53	402	U	+OH
Dihydroxy buspirone	0.55	418	U	+OH
Dihydroxy buspirone	0.55	418	U	+2(OH)
Dihydroxy buspirone	0.56	418	U		+2(OH)
Hydroxy buspirone	0.59	402	U	+2(OH)
Hydroxy buspirone	0.69	402	U	+2(OH)
Dihydroxy buspirone	0.70	418	+OH	+OH
Despyrimidinyl buspirone	0.74	308			-Pyrimidine
Hydroxy buspirone	0.74	402	U	+OH
Hydroxy buspirone	0.80	402	U	+OH
Hydroxy buspirone	O.87	402	+OH	U
Buspirone	1.00	386D>	U	U

(a) HPLC retention time relative to buspirone (RRT=1.00) using standard HPLC conditions. Buspirone retention time is 13.5 min.

(b) Molecular weight.

Under our previous metabolite analytical strategies, this level of structural information required weeks of work, however, the study above was completed in one day. In addition to increasing the speed of sample analysis, this strategy has allowed us to combine the analysis of 3-8 metabolite samples for automated analysis by taking advantage of overnight/unattended runs. Furthermore, the scientist's effort is focused on experimental planning, analysis and interpretation, rather than time-consuming tasks.

Natural Product Profiling

Natural products represent a valuable source of chemical diversity in the search for novel pharmacophores. Thus, accelerated methods for the rapid identification of novel natural products open new opportunities for novel therapies. An example of the rapid identification of natural products using LC/MS is the paclitaxel SPL. During development of the anti-cancer drug TAXOL®, for which paclitaxel is the active ingredient, we had the opportunity to utilize an LC/MS strategy to identify novel taxanes.

LC/MS analyses have been performed using a standard method on numerous natural extracts and process intermediates from the purification of paclitaxel from taxus brevifolia bark. From 5 to 30 trace taxane components are typically observed in each sample. A complete profile of the components is obtained, despite the chromatographic co-elution of several components, because of the combined mass resolution and chromatographic resolution. Table 2 shows part of the taxane structure profile library obtained by combining analytical information obtained from several samples. Combination of information was made possible because a standard method was locked-in early in the study and utilized for each sample. We have found that known taxanes in new samples can be rapidly identified by reference to the relative retention time (RRT) and MW of compounds in the structure profile library without further stages of analysis.

Table 2
Taxane Structure Profile Library

Taxane

PROPOSED STRUCTURE	RRT¹	MW²	R₁	R₂	R₃
10-DEACETYL BACCATIN Ill	0.08	544		H	H
BACCATIN III	0.16	586		CH₃C=O	H
7-XYLOSYL-10-DEACETYL CEPHALOMANNINE	0.22	921	C₄H₇	H	Xylose
7-XYLOSYL-10-DEACETYL PACLITAXEL	0.29	943	C₆H₅	H	Xylose
10-DEACETYL CEPHALOMANNINE	0.32	7119	C₄H₇	H	H
7-XYLOSYL-10-DEACETYL TAXOL C	0.35	937	C₅H₁₁	H	Xylose
10-DEACETYL PACLITAXEL	0.44	811	C₆H₅	H	H
7-XYLOSYL PACLITAXEL	0.49	985	C₆H₅	CH₃C=O	Xylose
10-DEACETYL TAXOL C	0.56	805	C₅H₁₁	H	H
10-DEACETYL-7-EPI-CEPHALOMANNINE	0.60	789	C₄H₇	H	H
7-XYLOSYL TAXOL C	0.62	979	C₅H₁₁	CH₃C=O	Xylose
CEPHALOMANNINE	0.72	831	C₄H₇	CH₃C=O	H
10-DEACETYL7-EPI-PACLITAXEL	0.82	811	C₆H₅	H	H
PACLITAXEL	1.00	853	C₆H₅	CH₃C=O	H
TAXOL C	1.05	847	C₅H₁₁	CH₃C=O	H
7-EPI-CEPHALOMANNINE	1.10	831	C₄H₇	CH₃C=O	H
7-EPI-PACLITAXEL	1.17	8.53	C₆H₅	CH₃C=O	H

(1) HPLC relative retention time.
(2) Molecular weight.

Combinatorial Chemistry

Chemical diversity is also introduced into drug discovery via combinatorial chemistry approaches. Traditional synthetic strategies have typically produced 10-20 new candidate drug molecules per synthetic chemist per year. Combinatorial techniques aim to increase this number to 1000-2000 per year. The traditional analytical strategy for chemical product confirmation utilizes an ensemble of techniques (i.e., elemental analysis, MS, IR and NMR). However, utilization of this strategy for combinatorial product characterization would require increasing analytical staffs, instrumentation and space by 100 fold. Our strategy for combinatorial analytical support emphasizes a standard LC/MS method. MW information provides for characterization of each mixture component. We have found that electrospray ionization and a selected mobile phase are effective for over 90% of the compounds we analyze. An on-line UV detector provides purity information for each mixture component. Networked information handling effectively handles large quantities of data. Automation of sample preparation utilizes Zymark Master Lab, System 5 and Easy-Fill modules. Autosampler systems provide for unattended instrumental analysis. Productivity enhancement has been benchmarked at 18 times traditional approaches.

Biomolecule Characterization

Although small drug molecules and biomolecules differ significantly in structure, we have successfully applied many of our small molecule analysis strategies for biomolecule characterization. Standard methods have been developed for the rapid characterization of proteins using polymeric µHPLC columns on-line with electrospray ionization MS. These methods have been used in our laboratory to obtain highly accurate molecular weight information for rapid confirmation of expressed protein sequences, assessment of covalent or post-translational modifications, and assessment of protein purity/heterogeneity. The system provides for complete automation of sample cleanup and analysis. Software, developed in Finnigan TSQ7000 Instrument Control Language (ICL), coordinates all aspects of sample and data handling (i.e., valve switching, sample injection, wash-solvent rinse, data acquisition, timing). These locked-in automated methods are now being used to analyze a diverse array of drug target and drug product proteins within a drug discovery and development environment. Reduction of manual sample handling steps via the automated on-line methods results in both savings of time and sample consumed. On-line micro-scale sample preconcentration and cleanup for LC/MS analysis of proteins and peptides provide high quality MW data (<O.Ol% error) obtainable at the 1-10 picomole level for large (>50 kD) proteins. The TSQ7000 Instrument Control Language (ICL) was used to automate the external devices and multiple steps involved with these methods. The on-line automated methods result in significant savings of time and precious sample through minimization of manual sample handling steps.

Figure 2
Automated On-Line Protein Desalting and Preconcentration System

Figure 3
Schematic of Instrument Control for Automated Sample Cleanup and Digestion

Crude protein isolate (total of 50 pmoles in 300 µL)
injected and pre-concentrated on trap

Figure 4
Automated Sample Clean-Up; Preconcentration of Dilute Samples

SUMMARY AND FUTURE PROSPECTS

Proactive strategies utilizing LC/MS techniques have been developed to facilitate the accelerated activities in pharmaceutical research, development and manufacturing. These have been successfully applied to routine analyses and benchmarked for productivity increases of 3 to 18 fold.

These strategies apply universally throughout pharmaceutical activities and provide increased levels of critical information than has been previously available. Application of these strategies is facilitating change in all collaborating pharmaceutical functions and providing competitive advantages in accelerated therapy development.

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