The FDA Critical Path to new Medical Products report (http://www.fda.gov/oc/initiatives/criticalpath/) recognised that improvements in knowledge management and transfer between research and development could provide critical productivity improvements and have significant impact on the successful development of new healthcare treatments. Translational research involving multi-directional knowledge flows between basic science and clinical research are hence a primary area for both future improvement and new approaches. Development and evaluation have not kept pace in recent years with advances in R&D technologies (e.g., genomics, microarrays, in silico) so as to enable better and earlier identification of novel targets, innovative therapies, safety risks, benefits or target sub-populations. It appears that new technology has been put into place in the R&D part of the pipeline without the ability to interpret and understand it in later decision-making.
Knowledge management approaches can help support improved performance in Critical Path areas of development and can help unite advances and diverse knowledge flows from genomics, systems biology, biomarkers, computational modelling, toxicology, pharmacology, diagnostics etc. with clinical trial design, operation and decision-making. New approaches to the use of information and communications technology and resources, in addition to increasing adoption of emerging knowledge management practices, both in explicit knowledge transfer and organisational development, could be increasingly applied to aid progress of drug, diagnostic and device development objectives.
On Monday 16th October 2006 a number of leading experts and practitioners will meet at the InnovationWell Community of Practice meeting at Bryn Mawr College, Philadelphia to discuss new applications of knowledge management and assessment in life science research and clinical development. I hope you can join the presentations and workshops followed by good conversations around the bbq!
I provide below a summary of the presentations and workshops.
Barry Hardy
Utilising Knowledge Management to increase R&D Productivity along Critical Paths
http://www.innovationwell.net/COMTY_kmrandproductivity/
InterAction Meeting Session, Bryn Mawr, Philadelphia, USA,
Monday, 16 October 2006
chaired by Michael Liebman (Windber Research Institute)
What a Quality Assurance Program can do to Facilitate Clinical Research and Development Process
Delia Y. Wolf, Harvard Medical School
The key to an efficient clinical research and development process is not only having a well-designed protocol, but also having a well-run clinical trial. As the majority of these clinical trials are conducted by investigators in an academic medical center, it is important to ensure that each participating investigator is well-informed about both scientific and regulatory requirements. In fact, a recent FDA report found that investigator noncompliance accounted for more than 70% of the deficiencies noted in the agency’s audit findings. One way to improve investigators’ understanding of and compliance with clinical research regulations and guidelines is implementing an effective quality assurance (QA) program that aims to improve investigator compliance with federal regulations, Good Clinical Practice (GCP) guidelines, and institutional requirements by providing on-site audit and assisting with investigator self-assessment.
The morning presentation will provide an overview of two practical QA approaches, namely onsite audit and investigator self-assessment, as well as their effectiveness in measuring compliance. The afternoon workshop will focus on a step–by-step guide to conducting an onsite audit and assisting investigators with conducting a self-assessment. Common findings of regulatory non-compliance in investigator-initiated study, as well as industry sponsored/CRO managed study will be covered. Practical tips on how to identify and avoid potential violations throughout clinical trials will also be discussed.
A Framework for Research Informatics
Peter Gates, Johnson & Johnson PR&D
We consider the question “What is research informatics?” We assert that the conceptual invariant across all research informatics is the scientific method. We define the scientific method as the interplay between observation and model construction. We take the position that model construction is generally not amenable to software automation. This we claim lies on the human side of the human-computer boundary. With that in mind we consider the following sequence of steps:
1. The mining of existing data
2. The planning of experiments
3. The execution of experiments
4. The reduction of observations to data
We propose the automation of these activities to be the program of research informatics. We focus on steps 2 though 4 and consider two specific strategies. The first is the use of partial evaluation of a function (f(b,x) = fb(x)) as a conceptual framework for combining convenience with flexibility in software. The second is the use of transitive closure (e.g. a->b and b->c => a->c) together with recursion as a convenient way of generating rich structures from a small set of simple building blocks. This last concept has been described as a free construction in the mathematics literature. These ideas will be illustrated with a design pattern for managing mixtures associated with biological assays used in pharmaceutical research.
Building an informatics infrastructure for translational research
Jonathan Sheldon, InforSense
Workflow has become a key technology for discovery informatics in life science research. Workflow technology enables scientists to dynamically construct their own research protocols for scientific analytics and decision making by connecting together various information resources and software applications in an intuitive manner. Workflow is not just a visual way of writing scripts for a vertical application. Workflow can form the foundation of an enterprise informatics environment enabling organizations to optimize their important data-driven processes and deliver information, expertise and derived knowledge effectively and quickly to decision-makers throughout the organization from scientist to the board.
Over the last couple of years we have also seen increasing investment in approaches that enable cross domain research both within major pharma and biomedical research centers. Strategies such as systems biology, pharmacogenomics, and biomarker discovery all have in common the requirement to access and integrate data and methods that cut across traditional silos: biology and chemistry, biology and clinical, chemistry and pre-clinical.
InforSense has combined advanced workflow technology with cross-domain analytics. Our integrative analytics platform has been engineered to effectively support translational research and addresses the needs of a diverse user community which ranges from biomedical informaticians to clinicians. In this presentation a variety of case studies will be presented with emphasis on examples which have a patient centric, clinically driven focus. In particular, we will describe in detail our work with Windber Research Institute to build a decision support environment that enables scientists to translate research into decisions that impact patient care. Specifically, we will describe how we have used workflow as a tool to:
* build a non disease specific clinical data warehouse
* provide a mechanism to browse this data (>600 fields per patient) and stratify into patient subsets e.g. responders vs non responders
* drill down into comprehensive views of all data collected for an individual patient
* integrate this clinical data in a dynamic manner with experimental data such as gene expression
* provide a powerful analytical environment to build predictive models of say treatment response which can reside in an Oracle database
* produce a simple web interface deployed into a customized portal to interpret the output of complex analysis for decision support
Why the “Top-Down Approach” to Knowledge and Content Management has failed the United Sates Intelligence Community – Implications for Healthcare Research
Duane Shugars, Concentia Digital
For the last 5 years we have witnessed hundreds of millions of dollars spent on large Enterprise Content Management (ECM) projects most of which have failed because too much time was spent on figuring out how a single piece of ECM technology was going to solve all the content management problems for the enterprise. The commercial space has long known that “Content” is king but the Government has been slow to understand this basic tenant of Content Management.
After millions of dollars and 4-5 years of effort, they look back on their ECM projects and realize that they have nothing more then a lofty architecture and an impressive search engine. What they lack, however, is the one thing that their ECM project was originally intended to help find ~Metadata and Content.
The owners of the content are now bound to using their local folders to manage their content, using tools such as MS Excel and MS Access as their primary tools to search and analyze data, and utilizing e-mail to share and collaborate. While each has a place in the organization’s value chain, all fall short of doing what they need to do to make the content manageable and thus the enterprise successful.
What went wrong and why?
What needs to be done to fix it?
Case Studies of success using the Bottom up Approach to enable the enterprise
What can the life science/healthcare sector learn from these efforts?
Research Information Management Systems for Translational Research
Jian Wang, BioFortis
The emergence of translational research as the paradigm for rapid conversion of knowledge attained from basic research through to clinical practice (and back) necessitates the development of flexible platforms to communicate across information silos. This talk will focus on the role of Research Information Management Systems (RIMS) in supporting translational research. Specifically, I will use our experience at the National Institutes of Health as a case study, supplemented by anecdotes from other academic institutions, hospitals and the private sector, to illustrate the unique challenges as well as lessons learned in this arena. I will discuss:
* How RIMS can fit into and support the translational research workflow, at the lab, project and enterprise levels
* Translational research must overcome a significant information gap – the gap between what is traditionally supported by Laboratory Information Management Systems (LIMS) and Electronic Medical Records (EMR)
* The participants in translational research and their different needs for and rights to information
* Translational research, by its very nature, demands collaboration and the need to manage institutional knowledge
* Regulatory compliance (patient privacy, data security etc) is a unique challenge given the different types of people and activities involved in a translational research program – I will use de-identification of Protected Health Information (PHI) as an example for discussion.
* The need for cultural changes in order to break down walls that hinder progress in translational research.
Applying Knowledge Assessment Techniques to Improving Productivity in Life Science Research
Barry Hardy, Douglas Connect & Jeff Spitzner, Rescentris
This presentation will discuss steps to be taken in the Knowledge Assessment of an R&D organization. Such an assessment initially obtains an overview of the current state of knowledge management in the organization and an identification of existing problem areas where actions could bring performance improvement. Areas to be investigated include knowledge gaps, bottlenecks, absence or under-utilisation of knowledge, lack of communication or collaboration, lack of access to or re-use of existing knowledge, difficulty in storing or retrieving knowledge, organizational or cultural issues, and barriers to knowledge sharing and innovation. The initial assessment can be subsequently followed by the introduction of new processes and tools as required, and a subsequent repetition of the assessment at periodic intervals as part of an ongoing performance improvement and support program.
The objectives of such a knowledge assessment and continuous improvement exercise are:
a) to assess the organization’s current situation and performance in a number of areas relating to the management and use of scientific knowledge and technical know-how;
b) to identify and prioritise areas for improvement in knowledge discovery, knowledge use and transfer and innovation;
c) to evaluate the effect that Electronic Lab Notebooks, Collaboration Support Systems and other IT and Knowledge Management tools is having, or is expected to have, on improving knowledge and innovation processes.
The benefits of such an approach are to:
* Allign R&D activities and knowledge processes with business strategies
* Improve productivity of R&D individuals and organisation
* Improve efficiency and reduce waste in R&D through knowledge loss or under-utilisation
* Increase knowledge sharing and innovation of R&D organisation
* Increase valuation of organisation through improved management of intellectual property and knowledge workers
* Improve quality of information captured from R&D processes
* Improve access to information captured from R&D processes
WORKSHOPS
Carrying out an Onsite Audit and Self-assessment in Clinical Trial Management
Delia Y. Wolf, Harvard Medical School
This workshop will focus on a step–by-step guide to conducting an onsite audit and assisting investigators with conducting a self-assessment. Common findings of regulatory non-compliance in investigator-initiated study, as well as industry sponsored/CRO managed study will be covered. Practical tips on how to identify and avoid potential violations throughout clinical trials will also be discussed.
Information Management Needs by Translational Researchers
Jian Wang, BioFortis
The emergence of translational research as the paradigm for rapid conversion of knowledge attained from basic research through to clinical practice (and back) necessitates the development of flexible platforms to communicate across information silos. In this workshop, we will re-trace the adoption process of Labmatrix™ by several institutes at the National Institutes of Health to support their translational research initiatives. These case studies demonstrate a set of unique information management needs by translational researchers as well as scientific administrators. The following will be discussed:
* The translational research process and its information management challenges at the lab, project and enterprise levels
* How is translational research different from basic research and clinical practice from an information management perspective
* How is translational research information managed today
* Who are the participants in translational research and what are their different needs for and rights to information
* Translational research, by its very nature, demands collaboration and the need to manage institutional knowledge
* What is a Research Information Management System (RIMS) and how does it differ from Laboratory Information Management Systems (LIMS) and Electronic Medical Records (EMR)
* Regulatory compliance (patient privacy, data security etc) is a unique challenge given the different types of people and activities involved in a translational research program
* The need for cultural changes in order to bridge the information gap that hinders progress in translational research
In addition to open discussions, workshop participants will have an opportunity to interact with a demonstration of Labmatrix™ and gain direct understanding of many challenges that NIH Labmatrix™ users encountered during their adoption of translational research information systems. Some examples are:
* Protecting patient privacy without stymieing research productivity
* Collaboration while maintaining oversight of your data
* Managing and querying patient specimen information, together with clinical information as well as research data (“-omics” etc) generated on the specimens
* Every lab/project is unique, how can a system serve them all
* Security Certification and Accreditation: software, network and human behavioral issues
* What does it take to get started
* System integration – fitting into the existing environment
* Training, support and maintenance
Knowledge Assessment in R&D – Impact on Project Management & Research Productivity
Barry Hardy, Douglas Connect & Jeff Spitzner, Rescentris
We will discuss Knowledge Assessment techniques and their impact on Project Management & Research Productivity from the following perspectives:
* Assessing organisational performance in the categories of Managing Records & Information, Finding Information, Finding Expertise, Organisational Development, Collaboration, Leadership, Knowledge Utilisation, Knowledge Transfer, Innovation, Project Management, Training, IT, and Support
* Methods for performing a knowledge assessment (e.g., surveying, interviews, knowledge mapping, benchmarking, organisational structure analysis, culture measurement, social network analysis, IT systems analysis, etc.)
* Measures for tracking performance improvement in organisational performance and innovation
* How to identify key areas of weakness, priority and importance identified for next improvement steps
* Processes, change, modifications, initiatives, training etc. required to implement improvement steps
* Selection of technologies, software systems, tools, ontologies, controlled vocabularies, etc., - and including both new approaches and modifications to existing systems - to enhance organisational performance, innovation and knowledge management
InnovationWell meeting workshop conference management executive
Bryn Mawr
Philadelphia
Critical Pathbiomarkers
metabolomics
toxicology
personalised medicine
KM Life Sciences Pharma Drug DiscoveryResearch and Development Drug Development Healthcare Innovation Knowledge Management events
InnovationWell Press Release (2 October 2006): http://www.prweb.com/releases/2006/10/prweb444155.htm
eCheminfo Press Release (29 September 2006): http://www.prweb.com/releases/2006/9/prweb443727.htm
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