A Multi-Disciplinary Approach to Impurity Identification, Elucidation, and Characterization

Ryan Sasaki, Graham McGibbon, Patrick Wheeler, and Michael Boruta Advanced Chemistry Development, Inc.

Toronto, ON, Canada www.acdlabs.com

CONTENTS

Introduction 1

The Importance of Chemical Context for the Identification, Elucidation, and

Characterization of Process Impurities and Degradation Products 3

Common Techniques and Specialized Tools for Impurity Characterization

and Elucidation 4

Specialized Tools for Mass Spectrometry 5

Specialized Tools for NMR Spectroscopy 7

Specialized Tools for Optical Spectroscopy 10

Bringing it All Together—An Electronic Platform for Collaboration and Reporting 10

Conclusion 11

Introduction

Unified Laboratory Intelligence (ULI) is a new category of laboratory R&D informatics that provides a

technology framework to improve chemical identification, characterization, and optimization for life

science, chemical, energy, consumer products, industrial, and technology industries. ULI is designed to

collect and unify chemical, structural, and analytical data as chemical content with context, which enables

the generation of intelligence from disparate information within a laboratory environment. In order for

any laboratory informatics solution to be implemented successfully and ensure productivity

improvements and clear returns, it must first be properly focused. “The most successful strategies are

likely to be those that address needs in the context of sub-disciplines.”1 As a result, this application note

will focus on the application of ULI within the context of impurity resolution within the drug development

process of the pharmaceutical industry.

Within the pharmaceutical industry, the rapid detection, identification, elucidation, and characterization

of synthetic or process impurities or degradants is an intense and comprehensive undertaking. Regulatory

agencies including the FDA and ICH mandate dose dependent thresholds for Reporting, Identification, and

Qualification of impurities. For example, in the development of a formulated drug substance, the FDA

requires that all impurities introduced in the proposed process above 0.1 by area percent need to be

isolated and structurally characterized (the requirement can be even lower for drugs with larger doses).

Impurities from synthesis, manufacture, or storage are all of interest. Furthermore, in order to develop a

robust drug product, degradation products must be characterized with the intent of minimizing their

presence (thus preserving the shelf life of the formulated drug product).

The identification, elucidation, and characterization of impurities and degradants in this environment

requires a multi-disciplinary approach which requires good communication and collaboration between

various groups. Through the entire drug development process a great wealth of chemical and analytical

information must be generated, collected, and documented to facilitate the identification, elucidation,

and characterization of impurities. Furthermore the trend toward a paperless environment facilitates the

management, dissemination, and rapid access to such large volumes of accumulated information.

Pharmaceutical Development groups (Pharm Dev or similar variants) are ultimately responsible for the

CMC (Chemistry, Manufacturing, and Controls) sections of Investigational New Drug (IND) applications

and New Drug Application (NDA) submissions. In general the groups involved in this process from a

synthetic chemistry and data collection and analysis point of view are (also depicted in Figure 1):

Process Chemistry—Process Chemists are responsible for developing the synthetic route for development candidates. They are expected to collaborate with the other groups below to facilitate the identification of impurities or to refine their synthetic route design to eliminate or minimize the presence of these impurities.

Analytical Research and Development—This group is typically responsible for the development of Drug Substance (DS) and Drug Product (DP) specifications. This group will work concertedly with the process chemistry and structure characterization groups in concert to enable impurity profiling and chemical stability evaluation with degradant identification. The “impurity profile” method is developed by Analytical R&D and this method is used to help identify all impurities through each stage of the synthetic route and to help the characterization group decide which impurities require structure elucidation and characterization. In this group, a significant amount of time, technology, and knowledge is also invested in method development, tests of robustness, and validation.

Structure Characterization Group—This group is typically responsible for performing the structure elucidation and characterization of impurities. In ideal situations, they work in close collaboration with the process chemistry and method development groups to ensure they can obtain a full sample history (‘context’) including the synthetic route, experimental conditions, solvents used, pH, temperature, etc. These groups most often work as interdisciplinary spectroscopy teams which bring a wealth of expertise in techniques like MS spectrometry, NMR and optical spectroscopies, and X-Ray Crystallography, amongst others. Elucidating and characterizing impurities in bulk drug substances and formulated drug products are one of their main responsibilities. (Note: the Structure Characterization Group is often a part of the Analytical Research and Development Group in some organizations.)

Figure 1: A summary of the groups involved in the impurity identification, elucidation, and characterization process in pharmaceutical development.

This application note will focus from the perspective of the third group described above—the Structure

Characterization Group and their evaluation of organic impurities, process related (e.g., reagents, ligands,

catalysts), and API/drug related impurities and intermediates (starting materials and byproducts). It will

also highlight the challenges existing in their environment along with the benefits of having a robust,

integrated, and instrument-agnostic software platform with tools designed to optimize their routine

process and assist in their most challenging tasks.

The Importance of Chemical Context for the Identification, Elucidation, and Characterization of Process Impurities and Degradation Products

When members of the structure characterization group receive a request for structure elucidation, there

is a variety of information about the unknown of interest that can help immensely in solving the chemical

structure in the most cost effective and time efficient manner. For example, knowledge of and access to

the synthetic route and reaction conditions might be the single most important piece of the puzzle for

process and route development samples.2 It will contain the starting materials for each step as well as the

intended product, solvents, and reagents used. In addition, the chemists working on the project may have

a short list of proposed structures that make chemical sense based on the starting materials used in the

reaction. When an impurity arises in the process this information can prove invaluable in helping the

spectrometrist and spectroscopists decide which experiments need to be acquired as a first pass as well

as which areas of their spectra they need to focus on.

Starting with this knowledge prior to an elucidation can save hours or even days of data acquisition and

analysis time and can improve cycle times and increase sample throughput. In addition, throughout the

long and evolving process of pharmaceutical development, circumstances arising from separation,

purification, and elucidation attempts may prompt the process chemistry group to refine and adapt their

original synthetic route. As the knowledge of these impurities (and their respective fates) grow through

multi-disciplinary discussion, the synthetic route can constantly evolve to help engineer these unwanted

impurities out of the finished drug product.

As a result, capturing the synthetic route as it constantly evolves in real-time and accessing the structures

and reaction conditions in an electronic environment should rank high in a list of informatics requirements

to help assist in their workflow to ensure clear and rapid communication streams. Furthermore, real-time,

fingertip access to this knowledge for all the scientists involved in the process can provide more

streamlined collaboration and better sharing of knowledge.

The ACD/Spectrus Platform allows the analytical chemistry group to easily access a sample’s history when

undergoing a new structure elucidation study, including analytical data acquired for current and past

projects, representative chromatograms and method conditions from the method development team, as

well the synthetic route, impurities already discovered, reaction conditions, etc. This information is

available as ‘live’ chemical and analytical information that can be modified, edited, or updated as the

synthetic route changes and evolves over the course of the project (Figure 2).

Figure 2: ACD/Spectrus DB can store the synthetic route as proposed by the Process Chemistry group, live chromatographic data from the method development group, and live analytical data by the structure characterization group. Within this view, the master synthetic route is viewable, and clicking on individual steps will reveal a table (bottom left) of already identified impurities. In addition, a master composite chromatogram (top right) is viewable that highlights the presence of the intended product, starting materials, and related impurities.

Furthermore, because all of the analytical data acquired is ‘live’, members of the structure

characterization group can re-analyze or re-process the data or import into their processing environment

for quick visual comparisons. Once this group identifies and characterizes a new impurity, they can easily

upload the chemical structure of the new impurity along with conclusions, notes, and interpreted spectra

to the currently established life cycle of the drug product. This helps put the data into the proper context

to provide an additional means of communication on the evolving story. This accumulation of knowledge

can prove invaluable to cross-functional teams as they tackle newly discovered impurities by easily

accessing the ‘live’ data associated with related impurities for easy comparisons and potentially faster

characterizations.

With the ability to constantly update and store all the information, data, and knowledge generated by the

structure characterization group and putting into the context of the process synthetic route, this creates

the initial foundation to assist in the rapid elucidation of an unknown impurity. This platform helps to set

up an ideal collaboration platform where knowledge of the chemistry is shared along with the associated

data.

Common Techniques and Specialized Tools for Impurity Characterization and Elucidation

Effectively navigating a new chemical entity from discovery to commercial relevance involves iterative

multi-step syntheses of the active pharmaceutical ingredient (API) on an increasing scale from grams to

kilograms with safety highly contingent on rapid comprehension and control of impurities. Such

understanding comes from the impurity and degradation profiles of sample batches built through the

unified interpretations, insights, and contextual information from the chemists and analysts throughout

the preparations and analyses. Therefore, representative detection of all relevant impurities in each

sample is essential, since it serves as the prelude to any identification and qualification. Analytical systems

and techniques must be sufficiently sensitive and selective to detect any impurities present in samples

above minimum thresholds designated by regulatory guidelines. Methods of impurity analysis need to be

comprehensive and robust, but, if possible, simple and cost effective. Therefore a variety of analytical

techniques may be used however impurity analyses inherently deal with mixtures so separation inevitably

plays a key role. Analytically, separations are most commonly accomplished using some kind of

chromatography. Modern chromatographies enable the resolution of hundreds or more components.

For the Structure Elucidation group, all the information discussed in the previous sections is incredibly

useful in helping them do their jobs most effectively. For the experts in these groups, details of how a new

impurity or degradation product was detected including chromatographic methods employed,

information pertaining to the synthetic route being utilized (in the case of a process impurity), or the

stability conditions that the molecule was subjected to in the case of a degradation product, is immensely

useful and the ideal starting point for any structure elucidation endeavor.3

However, while this wealth of information is invaluable, it is not enough to confirm the chemical structure

of an unknown impurity. In addition to this, elucidation experts must proceed with caution when using a

priori knowledge. While in most cases knowledge of starting materials, assumed chemistry, and related

impurities generally proves to assist in the interpretation, it can sometimes bias even the most

experienced elucidators, causing a mis-characterization.

These groups most often work as interdisciplinary teams that bring a wealth of expertise in techniques

like mass spectrometry (MS) and NMR and optical spectroscopies, amongst others. The make-up and

organization of these groups varies from organization to organization. While there are many analytical

chemistry techniques available, the three primarily applied for structure characterization in the

pharmaceutical industry for impurity characterization and elucidation today are mass spectrometry and

NMR and optical spectroscopies.

Specialized Tools for Mass Spectrometry

Mass spectrometry techniques with varying extents of sophistication are used by Process Chemists,

Analytical Chemists, and members of structure characterization groups for detection, identification, and

elucidation of structures. Identification can be facilitated by certain detectors so various hyphenated

techniques have become commonly employed, especially mass spectrometry combined with either gas

chromatography (GC/MS) or liquid chromatography (LC/MS), the latter generally with a UV-vis detector

(LC/UV). Low resolution GC/MS with 70 eV electron ionization is conveniently applied for some

compounds and is well-suited to residual solvent detection identification by comparing the spectrum of

an impurity to reference mass spectra, typically available in commercial or home-built spectral libraries.

However, the majority of compounds are polar enough to warrant LC/MS analysis, using electrospray or

atmospheric pressure chemical ionization.

For structure characterization, and tending toward more routine use for identification, advantage is taken

of high-resolution accurate mass systems that can reveal elemental compositions of compounds. Further

insights into impurity and degradant structures can come through their fragmentation behavior in MS/MS

and MSn experiments using various dissociation techniques. These valuable experiments enamor the use

of sophisticated equipment but also increase the complexity of data to be analyzed, so extracting and

managing this spectral knowledge is very important.

To facilitate mass spectrometry-based identification and characterization of impurities, the ACD/Spectrus

Platform includes advanced algorithms for finding components, whether known or new, and for

generating chemical formulae that match a specific mass or isotope distribution. To recognize known

components databases of mass spectra can be queried. Also, spectra can be interpreted and structures

assigned to MS/MS or MSn data with increased confidence through automated prediction or manual

assignment of fragment ions and pathways (Figure 3).

Figure 3: Figure showing key MS capabilities in LC/MS Workbooks.

Identification can be facilitated by certain detectors so various hyphenated techniques have become

commonly employed, especially mass spectrometry combined with either gas chromatography (GC/MS)

or liquid chromatography (LC/MS), the latter generally with a UV-vis detector (LC/UV). Low resolution

GC/MS with 70 eV electron ionization is conveniently applied for some compounds and is well-suited to

residual solvent detection identification by comparing the spectrum of an impurity to reference mass

spectra, typically available in commercial or home-built spectral libraries. However, the majority of

compounds are polar enough to warrant LC/MS analysis, using electrospray or atmospheric pressure

chemical ionization.

Despite all these capabilities, mass spectrometry often provides only partial evidence of structure with

the remainder deduced or inferred by comparison with peaks or spectra from other characterized

impurities, and from other chemical knowledge or data from other structurally informative techniques

like NMR.

Specialized Tools for NMR Spectroscopy

In cases where MS is not sufficient enough to solve a problem, or the result are inconclusive, acquisition

of NMR data and NMR analysis is the obvious next step. The types of NMR experiments acquired highly

depends on the preference of the NMR spectroscopist acquiring the data, but thanks in large part to

significant advancement and improvements in hardware (cryogenic NMR probe technology) very

information rich experiments are now more accessible on a routine basis. As a result of these advances,

the most common collection of data acquired for a structure elucidation by NMR include a 1H reference

spectrum, a 2D COSY experiment for homonuclear correlation information, as well 2D HSQC and HMBC

experiments for both direct and long-range heteronuclear correlation information. Depending on the

complexity of the problem, additional experiments such as NOESY, ROESY, and 1H-15N direct and long-

range correlation studies may be applied.

The key deliverable from the NMR group is a proof of structure report that details how and why the

proposed structure is consistent with all of the data acquired (Figure 4). Oftentimes, the spectroscopist

will need to differentiate between different stereoisomers and will need to conclusively highlight the key

aspects of the data that rule out the presence of one stereoisomer and the identification of another.

Figure 4: An example report output from ACD/NMR Workbook that details why the proposed structure is consistent with the data acquired.

ACD/NMR Workbook provides advanced processing and interpretation tools for NMR Spectroscopists

looking to deliver fast turnarounds on proof of structure reports. Detailed structure characterization often

relies on a multitude of NMR experiments, which poses a challenge when it comes to file organization and

retrieval. The process is made easy through the storage of related information in a data package, which

preserves the intimate connections between the data files and the proposed structure. The preservation

of these intimate connections are crucial as the software boasts a very fast and efficient peak picking and

assignment routine, enabling NMR Spectroscopists to transfer their knowledge to the system by

annotating structure-spectrum correlations that support a proof-of-structure. In addition to these

features, the software provides the Spectroscopist with assistance on data interpretation thanks to

embedded NMR prediction and verification tools. These tools can be enhanced by human knowledge thus

emphasizing the importance of assigning the data in an electronic environment. By hovering over a peak

in the 1D or 2D spectra, the software will suggest a proposed atom or correlation assignments to help

speed the characterization process (Figure 5).

Figure 5: When a peak is highlighted, the software suggests potential atoms that are consistent with 1H and 13C chemical shift information in addition to multiplicity and integration information from the 1D 1H spectrum, as well as long-range correlation information (when these experiments are available and included in the data package).

In most cases, when the spectroscopist has the luxury of access to the synthetic route and chemistry-

related information—details of the method such as findings from LC-MS analysis combined with the

appropriate NMR experiments—they can solve a structure relatively quickly. However, occasionally every

spectroscopist is challenged with a more difficult problem that requires a significantly longer time

commitment. This may be a case of a particularly complex molecule that is hydrogen-deficient (thus lacks

comprehensive long-range 1H-1H or 1H-13C coupling information. In other cases, the inability to distinguish

between two- and three-bond (and possibly four-bond) correlations introduces ambiguity that prevents

the spectroscopist from unambiguously confirming the chemical structure. In cases where nitrogen is

present, it can be quite useful to acquire a 1H-15N long-range correlation experiment, one that is much

more feasible today with the high-sensitivity associated with cryogenic NMR probes. In addition, there

are even more information-rich experiments such as the INADEQUATE and 1,1 ADEQUATE experiments

however they require a significant amount more sample and can take a long time depending on the

instrument setups available in the lab. Whether there are sample limitations, which is a very real challenge

in the drug development and impurity detection environment, or the ideal instrumentation is not

available, generally the last resort for the characterization group is to submit the sample for X-Ray

Crystallography analysis. Unfortunately, not all samples are amenable to these type of analysis as it

requires an adequate crystal of the material of interest which can be either impossible for some samples

or a very expensive and time-consuming process.

For many years, different Spectroscopists in the drug development laboratories have applied the use of

Computer-Assisted Structure Elucidation (CASE) technologies to serve as a reasonable alternative to X-

Ray for some of their more challenging elucidation requests.4,5,6,7,8 ACD/Structure Elucidator Suite is

without a doubt the most comprehensive and peer-reviewed software package for Computer-Assisted

Structure Elucidation.9,10 It is an extension on the ACD/NMR Workbook product described earlier. This

expert software system serves as a powerful analytical tool capable of assisting in the elucidation of very

complex molecular structures. The system serves as a great complement to the NMR spectroscopist as it

can mimic or accept his/her systematic knowledge and reasoning but also outperforms the human expert

in logical-combinatorial reasoning. The basic premise behind the technology is that it leverages

advancements in computer processing power and algorithm development to sift through all possible

structural candidates consistent with a given molecular formula. With these benefits the software can

identify for the spectroscopists only structural candidates that are consistent with all information

provided to the system. These outputs can be used in a variety of ways; 1) To increase confidence and

confirm that a proposed structure is consistent with all acquired data; 2) To evaluate additional structural

candidates that should be considered more closely; and 3) To evaluate whether additional experimental

data should be acquired to unambiguously confirm the identity of the impurity of interest. The track

record for ACD/Structure Elucidator Suite contains a long list of elucidation problems that were

considered either extremely challenging or unsolvable with traditional methods by an NMR Spectroscopist

(reference) and as a result it should be incorporated into any laboratory focused on the rapid identification

and characterization of impurities.

Figure 6: Explanation of the workflow for ACD/Structure Elucidator Suite. The software can input various types of analytical data and a molecular formula. Based on this information, a molecular connectivity diagram (MCD) is constructed and proprietary algorithms and database searches are combined to generate all structural candidates consistent with the supplied data. The final steps include full assignment of the NMR data to the chemical structure and a ranking suggesting the best possible matches.

Specialized Tools for Optical Spectroscopy

Although MS and NMR are the primary spectroscopic techniques used in structure elucidation, optical

spectroscopy (FTIR and Raman) is often used to provide complimentary information and in some cases

unique information to the problem. Optical spectroscopy also has the advantage of being highly sensitive

thus requiring small amounts of sample (compared to NMR), it is relatively easy to acquire the data, and

often the sample is recoverable.

The reproducible nature of spectra obtained on different instruments, along with a large body of

knowledge of spectrum-structure correlations, provides the background for functional group analysis; the

strength of optical spectroscopy in structure elucidation.

The ACD/Spectrus Platform includes a knowledgebase of spectrum-structure correlations for both IR and

Raman spectroscopy. The knowledgebase can be used in several ways to assist in the functional analysis

of a sample. A user can click on a peak in the spectrum to show a list of possible structure fragments,

search the knowledgebase itself, or if there is a proposed structure, simply highlight a portion of the

structure to show where those bands would be expected (Figure 7).

Figure 7: Green highlighting illustrates the possible band regions for the highlighted structure fragment

The ACD/Spectrus Platform is unique in that once an interpretation is made, a link between the structure

and spectral features can be created and saved with the spectrum, thus insuring this knowledge is saved

and available for the future.

Bringing it All Together—An Electronic Platform for Collaboration and Reporting

As discussed in the previous sections, a high degree of communication and collaboration between

scientists in a multi-disciplinary group is advantageous in helping to develop a drug impurity profile.

Having quick answers to questions like, What was the intended product? What are the starting materials

and reagents used? What are some related impurities we’ve already identified? What solvents were used?

etc., can prove instrumental in improving productivity in structure elucidation efforts. Throughout the

drug development process, and most importantly at the time of submission, progress reports,

presentations, and final documentation of the CMC sections for IND and NDA filings are required. The

preparation of this type of documentation can be very time-consuming and quite costly and disruptive, as

it requires collecting, collating, and combining representative data and chromatograms from various

stages of the entire process. All the data collected and associated with the impurity profile of individual

batches must be found, documented, and readily available if needed. In a typical scenario, it is not unusual

for hours/days to be spent searching for/compiling results of a series of specific analytical tests. Even

when the desired results are located it might be difficult to understand the context surrounding the data

representing the test. A worst-case scenario involves having to actually re-acquire data from samples if

previous test results cannot be located. In some cases this may even require re-purification of a sample,

or even worse, re-synthesis. Clearly activities such as this can be hugely disruptive, and most importantly,

costly due to delays in either NDA filing or response to an already existing submission.

The issues and time spent in the reporting process is not limited to searching for and finding relevant data.

Often times, once the data is located it still involves a laborious process of copy and pasting different

images from different data processing applications. Because of the vast array of analytical instrumentation

used throughout the drug development process, having to interact with different data processing

software applications and portals to access and re-plot data can be a very time-consuming and laborious

process. The major benefit of using ACD/Spectrus DB as a collaborative platform for data and knowledge

sharing is its ability to unify the ‘live’ analytical data from the significant variety of heterogeneous

instrument data formats in the typical laboratory informatics environment. As a result, if all the data and

its context is stored in one electronic environment, key information can be compiled and combined easily

and a report can be generated with the click of a button; saving days/weeks of time in report

compilation/creation.

The importance of ‘live’ data should not go unrecognized. When data is re-accessed and re-evaluated it

often will need to be re-processed, re-analyzed, or manipulated in some way. This cannot happen with

‘dead’ data stored as a PDF, or locked into a specific, proprietary instrument data format. In addition, a

‘live’ chemical and analytical data collaboration platform—ACD/Spectrus DB—helps compile all of the

chemical and analytical information into the context of the life cycle of the drug being developed. As

impurities arise, the Process Chemistry, Analytical R&D, and Structure Characterization groups have a

platform where they can quickly visualize and assess the context of a given impurity or a particular stage

in the process. The ACD/Spectrus Platform enables each scientist to dive deep into the context of the data

interpretation where they can evaluate not only the data associated with the chemical structure, but how

the data was assigned to the NMR, MS, and Optical data. This knowledge provides deep chemical context,

but also serves as the foundation to create a more intelligent informatics environment by leveraging this

knowledge to improve the algorithms being used routinely for various structure elucidation efforts.

This means that when these groups are contacted by regulatory personnel with requests for required or

additional information for regulatory filings, the information can be easily searched for, accessed, and

delivered in a timely fashion, avoiding any delays or re-run of experiments.

Conclusion

Data cultures in life science are very heterogeneous, and no single approach can suit the needs of

everyone. The most successful strategies are those that address needs in the context of sub-disciplines.1

Impurity Resolution Management (IRM) is an essential aspect of drug development where Unified

Laboratory Intelligence (ULI) can be successfully applied to improve decision-making, reduce time, and

decrease cost. As highlighted in this application note, the ACD/Spectrus Platform can serve to unify

analytical data from a variety of different instrument data formats and capture the knowledge through

chemical context by associating the data with the synthetic route and chromatographic method. Finally,

this knowledge base serves as the foundation for creating intelligence by enriching the key algorithms

used for structure elucidation and characterization with relevant human knowledge and interpretation.

1 Anne E. Thessen and David J. Patterson, Data issues in life sciences, PMC (NIH/NLM), http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3234430/, (November 28, 2011). 2 Paul G. Cummings, Priscilla Offen, Mark A. Olsen, Sonya Kennedy-Gabb, Gary Zuber, LC/MS, LC/NMR, FTIR: An Integrated Approach to Impurity Identification in Pharmaceutical Development and Formulation, American Pharmaceutical Review, 2003. 3 Gary E. Martin, Chapter 5: A Systematic Approach to Impurity Identification, Analysis of Drug Impurities, April 30, 2007. 4 Codina A., Ryan, R.W., Joyce R., Richards, D.S., Identification of Multiple Impurities in a Pharmaceutical Matrix Using Preparative Gas Chromatography and Computer-Assisted Structure Elucidation, Analytical Chemistry, 82(21):9127-9133, 2010. 5 K. A. Blinov, D. Carlson, M. E. Elyashberg, G. E. Martin, E. R. Martirosian, S. G. Molodtsov, and A. J. Williams, Computer-assisted structure elucidation of natural products with limited 2D NMR data: application of the StrucEluc system, Magn. Reson. Chem., 41:359–372, 2003. 6 M. E. Elyashberg, K. A. Blinov, E. R. Martirosian, S. G. Molodtsov, A. J. Williams, and G. E. Martin, Automated structure elucidation—the benefits of a symbiotic relationship between the spectroscopist and the expert system, J. Heterocyclic Chem., 40(6):1017–1029, 2003. 7 M. E. Elyashberg, K. A. Blinov, S. G. Molodtsov, A. J. Williams, and G. E. Martin, Structure Elucidator:  A Versatile Expert System for Molecular Structure Elucidation from 1D and 2D NMR Data and Molecular Fragments, J. Chem. Inf. Comput. Sci., 44(3):771–792, 2004. 8 S. G. Molodtsov, M. E. Elyashberg, K. A. Blinov, A. J. Williams, and G. E. Martin, Structure Elucidation from 2D NMR Spectra Using the StrucEluc Expert System:  Detection and Removal of Contradictions in the Data J. Chem. Inf. Comput. Sci., 44(5): 1737–1751, 2004. 9 Elyashberg, M.E., Williams, A.J., Martin, G.E., Computer-assisted structure verification and elucidation tools in NMR-based structure elucidation, Progress in Nuclear Magnetic Resonance Spectroscopy, 53(1/2):1–104, 2008. 10 Elyashberg, M.E., Williams, A.J., Blinov, K.A. Contemporary Computer-Assisted Approaches to Molecular Structure Elucidation. London: The Royal Society of Chemistry, 2008.