Knowledge Management in the pharmaceutical industry has been undergoing a transition over the past 5-10 years. With recent changes occurring in the industry, shifts in the research focus at both large pharmaceuticals and small-mid size pharmaceuticals and biotechs are becoming more common. The way we view the information food chain has had to change. We are in a world where we need to have greater flexibility and easier access to data than ever before. We are typically working with external as well as internal collaborators on our project teams.
On the 13 October 2008 at the InnovationWell Community of Practice Meeting at Bryn Mawr College, Philadelphia, we will run a workshop on the Push and Pull of Knowledge Management in R&D, which will be chaired by John Conway (Accelrys) and Frank Hollinger (Sphaera Pharma).
The objective of the workshop will be to discuss how Knowledge Management Systems are being developed in this new age, how they are being used and what changes we as a community should be pushing for in the next generation of systems. Keeping an eye toward doing things ‘right’ while remaining cost conscious, we are often presented with a challenge to put the ‘best’ system in place. Participants will discuss ways forward in solving this problem within organizations, collaborations and discovery teams.
User Perspectives will be used to seed discussions on current and future research needs in Knowledge Management in R&D support systems, which will be carried out using a wiki-supported Knowledge Cafe format.
Program & Schedule
09.00 Frank Brown (Accelrys), Data is only Valuable if you can Extract the Information
09.30 Chris Culberson (Merck Research Laboratories), WISK: What I Should Know – Mining Chemical Transformations to see What Really Works
10.00 Ralph T. Mosley (Pharmasset), Going Big to Small: What happens when you leave Big Pharma?
10.30 Coffee Break
11.00 Knowledge Cafe on Perspectives
12.30 Group Discussion
13.00 Lunch
14.00 Tim McIntyre (GlaxoSmithKline), Workflow Application Enhances Productivity
14.30 Chris Smith (Pfizer), Risk-based Decision Making based on Complex Physical Chemical, Environmental Fate and Toxicological Effect Data Sets for Pharmaceutical Products and their Intermediates
15.00 Barry Hardy (Douglas Connect), Knowledge-Oriented Collaboration in Virtual Organisation Structures
15.30 Coffee Break
16.00 Knowledge Cafe on Perspectives
17.30 Group Discussion
18.30 Knowledge-sharing Dinner
A description of the abstracts for the session perspectives follows:
The Push and Pull of Knowledge Management in R&D
http://innovationwell.net/COMTY_kmworkshopbm08
(Please follow continuation here to read abstracts. Comments can be made at the end.)
Abstracts
Data Is Only Valuable If You Can Extract The Information
Frank Brown, Accelrys
Knowledge Management (KM) is a ragging subject in most companies. The concept is that of using the intellectual capital of the company that resides in the personnel and the structured and unstructured data / information. However, there have been as many failed attempts as those that show some promise in the name of KM. The issue is always getting the right information at the right time in the right format. This allows the user to extract information and perhaps knowledge from the data being presented to her/him. The issue is almost always the lack of a common corporate data language / ontology. Some architectural concepts in how to approach this problem will be addressed.
WISK: What I Should Know – Mining Chemical Transformations to see What Really Works
Chris Culberson, Merck Research Laboratories
As screening technology improves, it is common to have large datasets to analyze and use for model building. In some cases, the additional data doesn't immediately provide more insight or better predictions. A WISK analysis can be used in these cases to provide a data driven path forward for a project team. WISK is based on the transformation analysis published by Sheridan et al JCIM – V46(1) p 180-192 (2006). Transformation analysis is a data organization technique not a QSAR method. The results of the analysis are a set of chemical transformations ranked by their success in solving the problem. WISK extends the analysis presented in the paper to include all pairs of molecules containing the same transformation. With this extension, one can present the user with an unbiased analysis of each transformation, including how many times a transformation has been tried, the chemical context (e.g. pair of molecules) and the effect on the assay outcome. With this analysis, a user can make an informed decision on the most applicable compounds for subsequent synthesis as well as knowing the historical probability of success for the transformation selected.
Going from Big to Small: What happens when you leave big Pharma?
Ralph T. Mosley, Head, Computational Chemistry, Pharmasset, Inc., Princeton NJ
Whether the result of “cost savings initiatives” or career development decisions, movement of personnel within the pharmaceutical industry seems to be increasing. One side effect is that “best practices” in knowledge management are migrating or being re-defined as a consequence of the new reality and the new job description in which the practitioner finds himself. The goal of this presentation will be to focus on the transition one may make in going from a large, multi-national pharmaceutical company to a much smaller pharmaceutical company.
To be clear: even though there is a difference in size, each of these companies is dedicated to discovering and developing disease therapies and has the same need to turn data into knowledge to help achieve those goals. Even so, there will be disparities between the amount of data available (and subsequently archived), human and financial resources that can be used to tackle the problem, and the speed with which those can be brought to bear. Relative to the number of targets each company may focus upon, these differences may actually not be so large at the end of the day.
Having been a molecular modeler for almost two decades at one of the top ten pharmaceutical companies with nearly sixty thousand employees and for the past year heading up computational chemistry at a company of about sixty, I am in the midst of making that transition between big and small Pharma. During the course of this presentation, I will reflect on what impact that thousand fold difference in headcount has by trying to answer these questions:
What are the similarities between these two companies in terms of data and knowledge management?
What are the differences between them?
How does one know what should be brought forward and what gets left behind?
How does all of this impact one’s career?
Also, some of the decision making process with regard to data and tools to access it that had preceded my arrival at Pharmasset will be touched upon. And finally, our ongoing effort to turn data into knowledge to help discover and develop new antiviral therapies at Pharmasset will be described.
Workflow Application Enhances Productivity
Timothy A McIntyre, Oncology Drug Discovery, GlaxoSmithKline, Collegeville
The investigation of ADME properties is resource intensive and complex, a common theme in pharmaceutical R&D. To simplify operations and increase productivity, we have developed a process-based application that has become the hub of our operation. The user interface employs Microsoft Access™; underlying data is stored in an Oracle database. The Resource And Tracking system (R.A.T.) is the single point of entry and retrieval for all study information. R.A.T. facilitates the full range of department activities such as requesting, assigning resource, scheduling and reporting of both internal and external studies. R.A.T. provides a mechanism for enhanced and transparent communication among study directors, staff scientists and management via automated email, shared schedules and linked documents. The functionality of R.A.T. has been augmented periodically, as business needs have evolved, to include automated internal effort and external expenditure tracking, metrics (by study director, compound, program, therapeutic area and study-type) and compound inventory. From 2004 to 2007 the database accumulated >300,000 rows of data representing ~8,700 studies and ~7,600 compounds. In 2007, department staff accessed the database >100,000 times (~8 per FTE per day). R.A.T. has reduced the resource needed to plan and execute DMPK studies, it has helped to identify bottle-necks in our operation and it has promoted real-time, continuous assessment of our efficiency. In summary, we describe herein the utility and value of a comprehensive workflow system that has the potential to be applied in other areas within pharmaceuticals to enhance productivity.
Risk-based Decision Making based on Complex Physical Chemical, Environmental Fate and Toxicological Effect Data Sets for Pharmaceutical Products and their Intermediates
Chris Smith, Pfizer
"The further back we look the further forward we can see." Winston Churchill
After countless years of asking, "Are these data available" and "where are they," we in Pfizer Global Environment, Health and Safety (PGEHS-EcoTox) have embarked on a different approach - Operation Coast Guard - Search, Sequester and Employ.
PGEHS-EcoTox requires a broad and complex data set (Physical Chemical, Environmental Fate and Effect (toxicological)) for all pharmaceutical products and their intermediates. These data are used to support internal and regulatory driven environmental impact and compliance. Historically this procedure is initiated five to seven years prior to the discovery of the pharmaceutical entity where resource allocations, compound availability and business practices are optimized. While efforts to identify experimental data were used it often suffered from manual review of 'known' data stores and re-keying of text bound reports - still significant arrays of these data were overlooked. Therefore, opportunities to evaluate these data (data mine) while also developing a standard approach for making justifiable and transparent decisions was seen as critical to our success as Environmental Toxicologists.
PGEHS-EcoTox is using a mission command approach (tasks based) to develop ecological manufacturing risk assessments. This approach employs the use of 'greedy acquisition' practices through a series of "protocols" to channel critical data to a 'federated' taxonomy. We use a Multi-Criteria Decision Analysis (MCDA) methodology to develop probabilistic determination of ecological impact and risk. Following a decision and analytical frame work Pfizer is combining scientifically defensible research and risk decision making to illustrate a balanced representation of risk and rewards by comparison to unknown variables. While still in development we believe that MCDA will allow visualization and quantification of the trade-offs involved in the Ecological Risk Assessment decision-making process. We feel this approach allows us to leverage information to minimize testing, reduce turn around times and provide a balanced risk based decision analysis.
Knowledge-Oriented Collaboration in Virtual Organisation Structures
Barry Hardy, Douglas Connect
SYNERGY, a new 3 year European-funded Seventh Framework Research Project which commenced on the 1 February 2008, researches the knowledge sharing and collaboration support needs of stakeholders working collaboratively within partnerships and new virtual enterprise network and virtual organization business models.
The next phase of enterprise interoperability is the controlled sharing of knowledge within collaborations and virtual organisations and networks to the mutual benefit of all partners. Such knowledge will be a driver for new enhanced collaborative enterprises, able to achieve the global visions of enterprise interoperability. The SYNERGY project envisages the delivery of Collaboration Knowledge services through trusted third parties offering web-based services, exploitable through interoperability service utilities.
Next generation network and service infrastructures will generate new economic opportunities with new classes of Enterprise 2.0 and Web 2.0 networked applications, whilst reducing operational expenditures. New utility-based service approaches are required to overcome the scalability, flexibility, dependability and security bottlenecks, of today’s network and service architectures which are primarily static and only able to support a limited number of devices, service features and limited confidence. Such new infrastructures will permit the emergence of a large variety of business models capable of dynamic and seamless end-to-end composition of resources across a multiplicity of devices, networks, providers and service domains.
New software-based services will need to be pervasive, ubiquitous and highly dynamic, and support a wide variety of nomadic interoperable devices and services, a variety of content formats and a multiplicity of delivery modes. They also have to support context awareness and the dynamic behaviour needed for applications with requirements that vary with time and context, and guarantee robustness, resilience, trust and security compatible with networks and software service platforms reaching a complexity and scale that are an order of magnitude greater than those of today’s infrastructures.
The overall aim of SYNERGY is to enhance support of the networked enterprise in the successful, timely creation of, and participation in collaborative structures by providing an infrastructure and services to discover, capture, deliver and apply knowledge relevant to collaboration creation and operation. Specifically SYNERGY aims to (a) provide semantic ontology-based modelling of knowledge structures on collaborative working; (b) develop the service-oriented self-adaptive SYNERGY holistic solution for knowledge-based collaboration services; and (c) facilitate the testing and evaluation of the efficiency and effectiveness of the SYNERGY solution in concrete case studies in business and industry.
Knowledge-oriented collaboration builds on state-of-the art research on Enterprise Interoperability. Data and information sharing are clear pre-requisites to application and interoperability of knowledge-oriented support for collaborative, virtual organisations. Process, service and enterprise models are fundamental: collaboration knowledge is knowledge of how to adapt and re-combine such models as business structures evolve. Small and Medium Size Enterprises increasingly are integral contributors and innovators in successful networks, and so methods and tools for Collaboration Knowledge Sharing must be accessible without major investment of capital or revenue for software acquisition, or of effort in developing skills to implement and use complex software tools. An Open Source approach to project-related software development on SYNERGY will be taken.
This presentation will focus on the user requirements that have been revealed in the first stage of the project research. These requirements reflect that many complex business, organizational and collaboration issues and challenges interact to guide practices and support services required for making collaboration more effective. The selection of effective practice and service approaches depend significantly on the context, culture and nature of the collaboration area and unpredictable events or complex issues arising. The implications for collaboration technology development imply that much more flexible and reactive support solutions are needed, and that even if we have such solutions, that overcoming culture challenges to collaboration are key ingredients for success.
Contact Information:
Program: Dr. Barry Hardy, InnovationWell Community of Practice & Research, Douglas Connect. Tel: +41 61 851 0170. barry.hardy -[at]- douglasconnect.com
Registration Enquiries: Nicki Douglas, Douglas Connect, Baermeggenweg 14, 4314 Zeiningen, Switzerland. Tel: +41 61 851 0461. InnovationWell -[at]- douglasconnect.com
or please visit:
http://InnovationWell-BM810.eventsbot.com
Barry Hardy
InnovationWell Community of Practice & Research Manager
InnovationWell KM Knowledge Management R&D bioinformatics Medicinal Chemistry Translational Medicine Molecular Medicine Molecular Modeling pharmaceutical pharma meeting workshop training Critical Path toxicology Life Sciences Drug Discovery Research and Development Drug Development Healthcare Innovation Innovation Management events
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