Philip Morris International deals with large quantities of scientific data from various sources in different formats. They developed an agile approach using microservices and graph databases to integrate data and provide a single interface for users. A prototype was completed by one scientist and developer in less than 3 months, called the ChemoInformatics KnowledgeBase, which assembles chemical constituent data and associates it with internal and public scientific studies.

1. Philip Morris International R&D, Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland
pmi.com, pmiscience.com
Agile Development and Fast Data Integration in a Large R&D Company
Antonio Castellon1, Pavel Pospisil2
1blue-infinity, Geneva, Switzerland, 2Philip Morris International R&D, Philip Morris Products S.A., Neuchâtel, Switzerland
Research and Development departments in large companies like Philip Morris International (PMI) deal with extremely large
quantities of data in a variety of formats, including primary scientific data, results from chemical, biological and toxicological
assays, and data from clinical investigations. All these data are recorded in different formats, derived from scientific and
laboratory management systems, data warehouses and documents. Now the question is, how do we provide users with a
convenient, single-point entry overview for all results… and fast?
Here we present an approach to perform data integration using the best technologies and architectures currently available,
including OSGi architecture combined with Micro-services, document and graph-based databases and web based user
interfaces.
The first prototype was completed by just one scientist and one IT developer in less than 3 months.
The product is named ChemoInformatics KnowledgeBase (CIKB). CIKB
is chemocentric database that (concretely within PMI) assembles data for
chemical constituents present in the aerosol of our products (e.g.
conventional cigarettes, e-cigarettes) and associates them with both
internal and publicly available scientific data. It is chemocentric since it
takes the most essential node of information related to the chemical
substance, however it can be expanded to any other-centric direction
later.
1. Concept 2. Architecture
3. Project Management 4. Conclusion
Pros
• Rapid development of new features
• Reduction in complexity with the use of separate services
• Highly flexible and adaptable environment enabling easy integration
of evolving user requirements using new languages and/or
frameworks from each service
• Easy to redistribute the services to several servers according to
computational and bandwidth requirements
• Easy deployment; only requires installation of new services and not
the full application
• The graph database allows better adaptability and flexibility in the
schema model than in traditional RDBMs
• A very good decoupled application between the view and data layers
using an AngularJS framework
• Easy redistribution of the work packages into future teams
Cons
• Requires a multidisciplinary developer or a group of developers with
skills in different environments (server, languages, frameworks, etc.)
• Although graph databases allow flexible model generation, it is crucial
to maintain regular discussions with scientists regarding the desired
model, to define the correct data type (node/relationship/property/etc.)
• The continuous integration of diverse data types derived from
different scientific disciplines requires an ongoing learning process
The architecture solution is an OSGi platform for core services,
incorporating Micro-services for the remainder, in order to manage
challenges (ambiguity, inconsistency, vagueness, incompleteness) due to
the complexity of the data models and the features required by the users.
Furthermore, it was essential to provide users with different interfaces
with the least effort required.
Less is More
According to the rule that “less is more,” the application development
started with minimal user requirements based upon common sense. The
complex features were defined as ‘epics’ in the tracking system JIRA. The
simple features were defined less formally within internal documents,
email communications and meeting notes.
CIKB
Graph Database
CHEMICAL CLUSTERING
CHEMOINFORMATICS
BIOINFORMATICS
CALCULATED
DATA
IN VITRO TOXICOLOGY
ANALYTICAL CHEMISTRY
IN VIVO TOXICOLOGY
SYSTEM TOXICOLOGY
PMI
MEASURED
DATA
PROPERTIES CALCULATION
AEROSOL PHYSICS
PRODUCT PORTFOLIO
FLAVOR & SENSORY DATA
AEROSOL CHEMISTRY
PMI
INTERNAL DATA
One comparative,
graphical,
user-friendly interface
FLAVOR PROPERTIES
REGULATORY LISTS
TOXICITY DATA
PUBLICLY
AVAILABLE DATA
CHEMICAL PROPERTIES
To be most efficient in communicating between the Scientific & Computer
worlds, two important roles were defined for this project:
As can be seen there is a high diversity of data types, including product
names, toxicities and calculated data, to name but a few. It requires a
degree of multidisciplinary knowledge and significant efforts to develop
the correct integration strategy for a single unique repository.
The architecture employed is robust, due to the fact that each service
is self-contained, having dependency upon other services only in the
case of security validation features. At the same time, it provides the
flexibility to create rapid solutions in response to user feedback, with
the ability to modify features or add technologies.
Scientific User 1
Scientific User <n>
. . .
IT dev. 1
IT dev. <n>
. . .JIRAUser req.
User req.
IT Leader
User + System req. = Tasks
Tasks
Scientific Leader
Feedback + bugs
SCIENTIFIC DOMAIN IT DOMAIN
Business User
. . .
Scientific Leader
In order to cover the diverse range
of scientific disciplines and also
to isolate the IT developers from
the complexity of scientific
understanding, this role acquires
the needs and wishes of scientists
and evaluates the priority for each
requirement from a business use
point of view.
IT Leader
In order to evaluate the complexity
for each new requirement, the IT
Leader will analyze each request and
propose solutions. Tasks are then
created and distributed to developers
in the form of work packages with
due dates. Finally, the Scientific and
IT leaders regularly check that the
solutions meet business needs.