I provide below a schedule for the upcoming InnovationWell and eCheminfo Community of Practice meetings at Bryn Mawr.
I also include a location map here which may be useful upon arrival:
Download bryn_mawr_campus_map_douglas_connect_meeting.pdf
[Please follow continuation here to view schedule.]
Current advances in computer-based predictive toxicology offer the potential to create more advanced environments for the screening and prediction of safety issues due to chemical and drug adverse side effects, drug-drug and chemical-system interactions, and chemical and drug toxicologies in the environment and the human body. Advances in this growing field also offer the potential to replace or reduce the need for animal testing and to reduce later stage clinical trial failures or new product development rejection. Acceleration of progress in practical applications requires the creation of interoperable environments, knowledge sharing, data integration, algorithm development, and extensive validation and testing.
Numerous opportunities exist in this field for scientific advances, but also for innovation, service and product development, and value creation. Additionally, significant collaboration approaches are a scientific, industry and society imperative to advance this field and the safety of new products and all society members. Collaborative approaches need to support the multidisciplinary networking and collaboration between computer scientists, biologists, chemists, toxicologists, product development and clinical and environmental researchers, and to network groups, centers, initiatives, projects and data into interoperable semantic frameworks, systems, knowledge bases and virtual organisations.
At our Predictive Toxicology session chaired by Artem Cherkasov (University of British Columbia) running 17 October 2008 at Bryn Mawr recent developments in the field of predictive toxicology will be presented and discussed.
The session will be preceded the evening of October 16 by a Knowledge Café to discuss Collaboration Opportunities in Predictive ADME & Predictive Toxicology.
A description of the session with presentation abstracts follows. Please add your comments, discussion or questions at the end of the post.
Predictive Toxicology
(Please follow continuation here to read abstracts. Comments can be made at the end.)
This year's InnovationWell Autumn Community of Practice Meeting will take place 14-17 October 2008 at Bryn Mawr College, Bryn Mawr, Philadelphia, USA to discuss the following areas of Innovation in Life Science & Healthcare R&D:
Critical Path Advances in Drug Development, Innovation & Knowledge Management in R&D and Translational Medicine, Computational Biology, Predictive ADME, Predictive Toxicology, Metabolomics, Biomarkers, Systems Biology
Program Summary
Systems Biology, chaired by Keith Elliston (Genstruct)
Computational Biology, chaired by Debraj Guhathakurta (Merck)
Knowledge Management in Translational Medicine, David Bousfield (Ganesha Associates)
Applications of Metabolomics to Drug Discovery & Development, chaired by Bruce Kristal (Brigham and Women's Hospital)
Predictive ADME, chaired by Anthony E. Klon (Pharmacopeia Drug Discovery)
Predictive Toxicology, chaired by Artem Cherkasov (University of British Columbia)
Pre-Conference Workshop, 13 October 2008
Knowledge Management in R&D
chaired by John Conway (Accelrys) and Frank Hollinger (FRESH Directions Consulting)
Speakers
Keith Elliston (Genstruct), Debraj GuhaThakurta (Rosetta Inpharmatics, Merck & Co.), Stephen W. Edwards (U.S. Environmental Protection Agency), Paul McDonagh (Gene Network Sciences), Christopher M.L.S. Bouton (Pfizer), James R. Brown (GlaxoSmithKline), John Wilbanks (Creative Commons), Barry Bunin (Collaborative Drug Discovery), Michael Liebman (Windber Research Institute), Jerry Wright (Johns Hopkins Medical Institutions), Anastasia Christianson (AstraZeneca), James Golden (Science Applications International Corporation), John Speakman (National Cancer Institute), William Hayes (Biogen Idec), Andrew McMurry (Harvard Medical School), Eugene Clark (Partners Healthcare), Alvin Berger (Metabolon), John Newman (USDA), Bruce Kristal (Brigham and Women's Hospital), Anton Hopfinger (University of New Mexico), Heidi Einolf (Novartis), Yojiro Sakiyama (Pfizer), Olga Obrezanova (BioFocus DPI, UK), Anthony E. Klon (Pharmacopeia), Artem Cherkasov (University of British Columbia, Canada), Ann Richards (US EPA), Curt Breneman (RPI), Alex Tropsha (UNC), Barry Hardy (Douglas Connect), Weida Tong (FDA)
CFP
We invite contributed papers from members of academic, government research and commercial organizations on areas of new research and innovation relevant to innovation and knowledge management in the life sciences. The work presented should involve innovative new method development or application in the areas of systems biology, translational medicine, knowledge management, computational biology, metabolomics, predictive ADME, predictive toxicology or bioinformatics. Studies including experimental work in medicinal chemistry, screening, experimental toxicology, pre-clinical evaluation, lead optimisation and translational medicine are welcome.
Abstracts (300-500 words) should be submitted to innovationwell -[at]-douglasconnect.com by 31 July 2008, and be accompanied by a short biography of the presenting author (300-500 words). Abstracts approved by the scientific organizing committee will be selected for scheduling on the conference program and in meeting poster sessions. Authors will be notified of acceptance as soon as a review of submitted materials takes place and at the latest by 15 August 2008.
Bursary
Bursary Awards will be used to support the attendance of a selection of academic young investigators at the meeting and workshops. Applicants should be working in a relevant area of research related to life science, healthcare, and drug product discovery and development at the postdoctoral, graduate student and senior undergraduate levels.
To apply for the bursary please send an email with a) your abstract and biography (300-500 words each), b) your CV of 1-2 pages, c) a short description of your interests and career motivations related to R&D (300-500 words) to innovationwell -[at]- douglasconnect.com by 31 July 2008. The recipients of the bursary awards will be selected based on an evaluation of the quality and innovation of the described research and the potential positive impact of attendance at the meeting on their research and career progress. Authors will be notified of acceptance by 15 August 2008.
Poster Session
All InterAction Meeting registrants are eligible to present a Conference Poster. The Poster Sessions will take place in the evenings in Thomas Great Hall on campus, where refreshments and dinner are also served. Poster Abstracts (300-500 words) with Title, Institution, Authors and Contact Information should be submitted to barry.hardy -[at]-
douglasconnect.com Abstracts will be considered based on date of submission and quality, and will be reviewed and accepted as they are received. To be considered for the formal program, they should be submitted at the very latest by 31 August 2008.
Download Program Brochure as pdf:
Download InnovationWell-BM08-Final1.pdf
Contact:
Program: Dr. Barry Hardy, InnovationWell Community of Practice, 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:
InnovationWell meeting Computational Biology Translational Medicine Systems Biology ADME Predictive ADME Predictive Toxicology Innovative Medicines Community of Practice workshop conference management executive Bryn Mawr Philadelphia Critical Path biomarkers metabolomics toxicology personalised medicine KM Life Sciences Pharma Drug Discovery Drug Safety Research and Development Drug Development Healthcare Innovation Knowledge Management events
On the 17-19 October 2007 we will host a joint
eCheminfo and InnovationWell Community of Practice Workshop and Forum at Bryn Mawr College, Philadelphia to discuss and advance
best practices in predictive ADME and Toxicology, to develop best practices for
comparison studies and validation, to review latest developments in method
development and applications related to drug discovery and development, and to
discuss the potential for collaborations between initiatives and international
cooperation.
This conference, forum and
workshop activity will consist of the following parts:
1. Workshops to discuss developments, challenges and potential for collaborations. (afternoons of October
17-19).
2. Conference
sessions on latest ADMET methods and application developments with
presentations and panel discussions. (mornings of October 18 and 19)
3. Hands-on Workshop
sessions with drug discovery informatics software (running during afternoons throughout week)
4. Evening Poster Sessions on latest modelling
developments (evenings of October 17 and 18)
Workshop
Facilitators
Joseph Tomaszewski (NCI), Artem Cherkasov
(University of British Columbia), Dennis Pelletier (Pfizer), Richard Beger
(FDA), Anthony Klon (Pharmacopeia Drug Discovery), Tony Hopfinger (University
of New Mexico College of Pharmacy), Joseph Contrera (FDA), Christoph
Helma (University of Freiburg and in silico toxicology), Vladimir Poroikov
(Russian Academy of Sciences), Judith Madden (Liverpool John Moores
University), Ann Richard (EPA)
(continued ...)
Continue reading "Advancing best practices in predictive ADME and Toxicology" »
A variety of initiatives of relevance to the development of ADME/Toxicology resources of value to supporting improved productivity in drug discovery and development are in progress in different organisations and countries. There is potential for great benefits for collaboration and alignment between such initiatives so as to support the robust development of the emerging field of predictive toxicology and to advance goals related to heathcare safety and development as expressed in the FDA's Critical Path Initiative in the USA and the EU's Innovative Medicines Initiative in Europe.
To further development and progress in this area we are scheduling the following activity:
International Forum & Workshop on Cooperation on ADME/Tox
18-19 October 2007
to take place at the Community of Practice Meeting, Autumn 2007
a joint InnovationWell and eCheminfo InterAction Meeting
Bryn Mawr College, Philadelphia
http://www.echeminfo.com/COMTY_conferences
This forum and workshop will have an agenda developed by workshop leaders to address ways forward for international cooperation and including discussion of the following topics:
The agenda of the forum and workshop will be designed by a set of workshop leaders so as to maximise interaction, discussion, issue resolution, and action plans for cooperation. In addition to presentations on latest developments, workshop activities will address specific challenges to progress in the field and areas where collaboration can support integration and alignment of programs and resources and reduction of duplication. An Innovation Cafe format will be used in which the group will define a scenario in which optimum confidence in predictive toxicology methods has been reached and will then prioritize steps for achieving that goal. The resulting roadmap should provide action plans where cooperation between initiatives can accelerate the contribution of predictive toxicology methods to enhanced confidence in safety of new healthcare products and progressing the goal of reduction and replacement of animal testing by computational methods. Virtual communication and collaboration approaches will be used pre- and post-event to maximise the benefit of the workshop.
Workshop leaders are being invited from the US and Europe and will include representatives from industry, government and academia.
Barry Hardy
Community of Practice Manager
eCheminfo InnovationWell cheminformatics chemoinformatics bioinformatics Medicinal Chemistry Computational Chemistry Virtual Screening ADME ADMET toxicology Molecular Modelling Molecular Modeling pharmaceutical pharma meeting workshop training Oxford Critical Path toxicology Bursary Life Sciences Pharma Drug Discovery Research and Development Drug Development Healthcare Innovation Knowledge Management events
During November I will be planning the program for the following InnovationWell workshop in Oxford (cross-industry sector) and InterAction Meeting in Bryn Mawr (life science/pharma/healthcare sector). Please contact me with your interests and proposals!
Knowledge Assessment & Performance Improvement of Collaborative Work and Innovation Activities
InnovationWell Workshop & Innovation Café, accompanied by pre-meeting
2 day hands-on workshop activities on collaborative systems and ELNs
20-22 June 2007, Oxford University, Oxford UK
Innovation in Life Science & Healthcare Research & Product Development
InnovationWell Community of Practice InterAction Meeting
15-18 October 2007, Bryn Mawr College, Philadelphia, PA, USA
Themes: FDA Critical Path Themes, Knowledge Management, Translational Research, Biomedical Informatics, Metabolomics, Biomarkers, Toxicology, Patient & Drug Safety
InnovationWell Gold membership
This entitles members to access InnovationWell meeting proceedings including audio, access to our Executive Insights reports from meeting and community of practice activities, and additional member discounts on meeting and training registration fees.
Download InnovationWell2007MembershipForm.pdf
Barry Hardy
Email: barry.hardy *[at]* douglasconnect.com
InnovationWell meeting workshop conference management executive Bryn Mawr Philadelphia Critical Pathbiomarkers metabolomics toxicology personalised medicine KM Life Sciences Pharma Drug Discovery Drug Safety Research and Development Drug Development Healthcare Innovation Knowledge Management events
Metabolomics is an FDA-identified Critical Path Opportunity (1) offering a toolkit which can be potentially applied to identification of safety biomarkers, diagnostic monitoring of patient response to drug treatment, lead optimization through toxicity assessment in non-clinical drug development, biochemical pathway studies in cells, animals and humans, patient stratification, and insights on and tracking of mechanisms associated with the onset of disease or following therapeutic intervention.
However, despite its above promise, the challenges in the complexity of the biological systems studies, the experimental spectroscopy methods used and the datasets generated has restricted to this point the full commercial application of metabolomics methods in the pharmaceutical industry and in healthcare.
The complexity of the interpretation of metabolomics data points to the need for improved data analytics and visualisation methods in decision making processes and situations (2). The importance of the value-added of the integration of metabolomics data with other proteomic and genomic data to provide a more integrated, accurate and broader view of the state of the biological system studied points to the importance of explicit knowledge management techniques in critical path areas of clinical research and drug development (3) to the application of semantic web, ontology and web service approaches (4) and to the adoption of these approaches in the day-to-day scientific research activity as supported by electronic laboratory notebooks and collaboration systems (5). It also points again to the importance of co-operation on the always difficult agreement area of the definition of standards and data integration.
I also find it quite interesting that two different fields (knowledge management and metabolomics) share a common critical concept: that of context. Context is critical in the human area of knowledge management and transfer in social ecosystems and its poor treatment a reason why many early IT and informatics approaches to knowledge management worked poorly. In the biological situation of a cell or animal, metabolomics provides the critical biochemical context and data to match it, and can do so in a dynamic way over time and can track perturbations in the behaviour of such a complex system.
Recent progress in the metabolomics field includes new advances in spectroscopic and statistical and analytical techniques that strengthen and expand the accuracy and scope of the analysis possible. But the progress also increasingly includes significant application experience which already has included a significant role in the 2005 Nobel Prize in Medicine award for assigning the causative role of H. pylori bacterium in peptic ulcers and gastritis, and more recently has been applied to patient stratification in Lou Gehrig’s disease, identification of off-targeted side effects for several drugs and new chemical entities, has been applied in diagnostic roles on serum samples of diabetics and non-diabetics, the development of biomarkers for prediction of drug-induced liver injury and to insight into toxic effects from urine analysis.
Richard Beger (FDA) has pointed out (6,7) that the development of NMR- based multi-dimensional quantitative spectrometric data-activity relationships (QSDAR) provides models which could be useful for estimating chemical toxicity, risk assessment of environmental contaminants and drug-lead identifications, and that such models of biological activity should be more objective and overcome some of the unreliabilities of traditional Quantitative Structure-Activity Relationship (QSAR) approaches (8). He also indicates that Metabolomics can play an important role in the creation of better evaluation tools and models for diseases, better identification and quantification of safety biomarkers, and improving the measurement of patient response. The voluntary submission of genomics data (VGDS) to the FDA is now accepting both proteomics and metabolomics data sets (9).
In response to such demand and interest, and in addition to significant activity in academic research, a number of companies including Metabolon, Leco, Blue Gnome, Bio-Rad and Chenomx are increasingly offering commercial solutions and services in metabolomics to industry.
I provide below a description of the presentation, discussion and workshop activity for the InnovationWell Session on Application of Metabolomics to Drug Discovery & Development which will take place on Wednesday 18th October ’06 at the InnovationWell meeting at Bryn Mawr. (Follow the Continuation…)
Barry Hardy
References
1. FDA Critical Path Opportunities Report, http://www.fda.gov/oc/initiatives/criticalpath
2. Decision Support in Drug Discovery & Development, http://barryhardy.blogs.com/theferryman/2006/09/decision_suppor.html
3. Knowledge Management in Translational Research, http://barryhardy.blogs.com/theferryman/2006/09/utilising_knowl.html
4. Semantic Web & Drug Development, http://www.innovationwell.net/COMTY_semweb/
5. KM in R&D and ELNs, http://www.innovationwell.net/COMTY_conferenceopenevent/
6. Richard D. Beger, Drug Discovery Today, Vol. 11, pp 429-435, May (2006).
7. R. D. Beger, D. A. Buzata, J.G. Wilkes, Drug Discovery Handbook, Ed. Shayne C. Gad, John Wiley & Sons, pp 227-285 (2005)
8. Predictive Toxicology, http://barryhardy.blogs.com/cheminfostream/2006/09/appyling_predic.html
9. FDA’s Critical Path Initiative: Opportunities for Metabolomics http://www.innovationwell.net/COMTY_mebegerr/
(continued…)
I summarise here what I think are three interesting questions & discussion topics for progress in current chemistry and informatics research in Drug Discovery & Development.
Computational chemistry methods have now been applied with success and significant contributions to drug discovery research and development. Nevertheless current methods are not yet able to comprehensively or easily meet the needs of medicinal chemists, or on certain kinds of problems are failing or have challenges or complications. We ask the question:
Where do we currently stand with cheminformatics-driven medicinal chemistry?
More at http://barryhardy.blogs.com/cheminfostream/2006/10/where_do_we_cur.html
(This includes a presentation and discussion of the discovery and development of low molecular weight non-peptidic beta-secretase inhibitors as potential new therapeutics against Alzheimer's Disease.)
After twenty years of undeniable progress, molecular docking seems to have plateaued. A recent paper by Tirado-Rives and Jorgensen [1] dashes some of the few hopes we had left by showing that conformational energetics alone make it impossible to rank order diverse compounds in high throughput virtual screening. In a Perspective in the same issue [2], Leach, Shoichet and Pieshoff summarize the stagnating state of the art that is docking, and suggest a pragmatic way forward, through measurement and benchmarking. Again in the same issue, a laborious evaluation of 10 docking programs, using 37 scoring functions was applied to seven protein types for three tasks: binding mode prediction, virtual screening for lead identification, and rank-ordering by affinity for lead optimization [3]. Among some encouraging results and upbeat analysis, the paper makes a number of worrying observations, including that "high fidelity in the reproduction of observed binding poses did not automatically impart success in virtual screening". Moreover, for eight diverse systems, "no statistically significant relationship existed between docking scores and ligand affinity."
John Irwin and I are asking the following question:
Could we take a Community Approach to Comparing Virtual Screening Methods?
More at http://barryhardy.blogs.com/cheminfostream/2006/10/could_we_take_a.html
The ability to make informed decisions during the early phases of drug discovery is the key to decreasing hit-to-lead and lead optimization cycle times. The motto “fail early, and fail cheap” represents the need to identify problematic chemotypes early in the development process so that more productive lines of inquiry may be followed. The field of predictive modeling has reached a point where there is a realistic expectation that troublesome moieties can be flagged through computational virtual screening. The next major step in the development of predictive methods is to be able to also use these modeling techniques to suggest productive courses of action to identify and correct ADME and PK problems during lead compound optimization. Thus, the use of validated, interpretable models may serve both as a way of identifying ADME/Tox and PK failures, and also provide a means for correcting them. Predictive Toxicology is therefore one area that potentially can contribute significantly more in the future than it has in the past to improving our confidence in the safety of new drug candidates in clinical development [6].
We ask the question:
How can we improve our Confidence in the Drug Safety of potential new Therapeutics through Predictive Toxicology?
More at: http://barryhardy.blogs.com/cheminfostream/2006/09/appyling_predic.html
Barry Hardy
References
[1] Tirado-Rives & Jorgensen, Contribution of Conformer Focusing to the Uncertainty in Predicting Free Energies for Protein-Ligand Binding, J. Med. Chem, 2006, 59,5880-5884.
[2] Leach, Shoichet, Pieshoff, Prediction of Protein-Ligand Interactions. Docking and Scoring: Successes and Gaps., J Med Chem, 2006, 49, 5851-5855.
[3] Warren et al, A Critical Assessment of Docking Programs and Scoring Functions, J Med Chem, 2006, 49, 5912-5931.
[4] http://www.nigms.nih.gov/News/Reports/DockingMeeting022406.htm
[5] Huang, Shoichet, Irwin, Benchmarking Sets for Molecular Docking, J. Med. Chem, 2006, in press.
[6] B. Hardy, P. Elkin, J. Averback, A.L. Fontaine, S. Kahn, Improving Confidence in Safety in Clinical Drug Development: The Science of Knowledge Management, The Monitor, Association of Clinical Research Professionals, p. 37-41, October 2006.
InnovationWell eCheminfo cheminformatics chemoinformatics bioinformatics Medicinal Chemistry Computational Chemistry Virtual Screening Docking Molecular Modelling Molecular Modeling pharmaceutical pharma meeting workshop conference management Bryn Mawr Philadelphia Critical Path toxicology personalised medicine Life Sciences Pharma Drug DiscoveryResearch and Development Drug Development Healthcare Innovation Knowledge Management events
The FDA has identified the development of new biomarkers as one of the key opportunities to increase efficiency, predictability, and productivity in drug development. I provide below a description of the presentation, discussion and workshop activity for the session on Biomarker Discovery & Applications in Drug Development which will take place on Thursday 19th October ’06 at the InnovationWell meeting at Bryn Mawr.
The session on the application of biomarkers in drug development will explore new advances and challenges in this area and will include a keynote from Keith Elliston, CEO (Genstruct), with Zentam Tsuchihashi (BMS) discussing Biomarker Roles in Tumor Immunotherapy, Darius Dziuda (CCSU) will cover the topic of Multivariate BioMarkers, Michael Jones (Novartis) will discuss Proteomics applications whereas Bernd Bonnekoh (Otto-von-Guericke University) and Ansgar J. Pommer (SkinSysTec) will provide perspectives for Multi Epitope Ligand Kartography (MELK) and skin disease applications. This latter work is being published in Nature Biotechnlogy and is featured on its mid-October cover.
Full abstracts are provided below.
Barry Hardy
(continued…)
Continue reading "Biomarker Discovery & Applications in Drug Development" »
The data created during drug discovery and development and from clinical research programs is great in volume and complicated in diversity. Additionally, both biological systems and chemical interventions in them are complex, as are the human, medical, industry and regulatory environments in which programs are created and carried out. Hence gathering together and processing all relevant sources of knowledge at any time in which a decision needs to be made is by its nature very difficult.
Selection and visualisation of the most relevant data required for insights and decisions is a challenging area to which increasingly sophisticated analytics tools are being applied. Concept mapping, knowledge maps, natural language processing of unstructured information, semantic classification and ontologies, and sophisticated visualisation tools all offer approaches which can be helpful in this area. Nevertheless, many knowledge management issues remain challenging in both the management and availability of information and in the selection and use of processing tools.
Systems biology approaches attempt to unify diverse data and models about complex cell behaviour so as to enable the study of a complex subject such as cell or organ toxicity. Modern analytics tools and data mining provide researchers tools to interactively explore such biological information and to test hypotheses about their data, and to ask new and interesting questions arising from it.
Risk management has been seen by regulators and industry as an increasingly important methodology and the incorporation of risk-based approaches into decision making around product safety issues and clinical trial management is a current vital area of practice development.
Electronic lab notebooks systems are currently offering a better start in how we initially record our experimental scientific information and such improved initial record keeping and semantic frameworks offer the potential for improved knowledge transfer and re-use at subsequent decision making points.
On Tuesday 17th October 2006 we will discuss these important current topics in decision making as applied to drug discovery and development and clinical research at the InnovationWell Community of Practice meeting at Bryn Mawr College, Philadelphia. In the addition to the morning conference session, workshops will run in the afternoons and from 4pm we will runs a series of demonstrations, a panel discussion and a knowledge café into the evening hours to share insights on problems and solutions in this complex but important area.
I provide below a description of some of the presentations and workshops.
Barry Hardy
Decision Support for Research & Development
http://www.innovationwell.net/COMTY_decisionsupport/
InterAction Meeting Session, Bryn Mawr, Philadelphia, USA,
Tuesday, 17 October 2006
chaired by Dennis Underwood (Praxeon)
The Role of Systems Biology and Knowledge Management in Advancing Toxicology Knowledge in Big Pharma
Peter V. Henstock, Pfizer
This talk will focus on two key research areas of the Systems Biology group at the Pfizer Research Technology Center in Cambridge, Massachusetts. The first area involves efforts to identify indications of hepatic injury using a set of cell-based assays. Panels of compounds with known toxic endpoints have been assembled and screened to characterize hepatic toxicity using a variety of assays. The second area is an effort to model the p38 signaling pathway associated with rheumatoid arthritis. A combination of literature mining, cell-based assays, and mathematical modeling of the pathway has been used with the goal of better understanding the associated toxicities. The approaches and challenges of both areas will be presented.
Case Studies in Using Interactive Visual Analytics to Accelerate Drug Development
David Mosenkis, Spotfire
Pharmaceutical R&D is a data-intensive process. While computer-assisted instruments and analysis tools are ubiquitous at all phases, research teams are often compelled to make key decisions based on limited analysis and reports that reflect only discrete islands of information in a vast sea of data. By integrating access to disparate types of data, and by applying interactive visualization and exploration of information, decision makers can gain the insights needed to make better-informed decisions. Visual analytics is an approach that allows users to interactively explore information, form and test hypotheses, and get immediate answers to questions about their data.
We present examples from several stages of the R&D process that illustrate how visual analytics can help researchers make better decisions earlier in the process:
* High-throughput screening: diagnosing systematic quality problems
* Lead optimization: discovering correlations between structure, biological activity and ADME properties
* Clinical trials: uncovering early indicators of drug safety issues
We conclude with an overview of the Spotfire DecisionSite platform, and show how it enables improved decision-making at all levels of the enterprise.
Searching for Answers: the game of twenty questions
Dennis Underwood, Praxeon
Curing human disease is one of the most challenging of human endeavors. Despite advances in drug development and our deeper understanding of medicine it has become increasingly difficult to bring new drugs to market. From discovery to market, drug development is an odyssey through an information maze; every path to success is obscured by dead-ends. Selecting a new disease therapy or extending current indications is a difficult process involving decisions about the likelihood of success, competition challenges and the value of the opportunity to the current portfolio.
Despite the dramatic increase in data and information generation, it has become increasingly challenging to bring new drugs to market. Paradoxically, the mass of new information has served to confound rather than to enlighten. In other industries, the use of sophisticated information technology has transformed processes, increased efficiency and created innovation. Pharma and Biotech are knowledge industries and yet there are very few tools available that increase the efficiency of the transformation of data to information to knowledge.
Even with sophisticated new technologies, the challenges of the complexity of data-types and problems associated with building models of understanding disease therapies that are based on inherently complex and variable biological systems remain. I will describe some of these challenges and highlight new methods that have the potential to revolutionize the way in which data and information are used within the industry. This is the beginning of a new era in which searching for answers in the information that surrounds us becomes as facile and as enlightening as dialog with a mentor.
Management Reporting of Clinical Trial Programs, Portfolios, and Studies: Managing Risks / Managing Projects
Joel Hoffman, Insightful
Managing a clinical trial is managing risk. In this presentation, the types of risk that companies and academic institutions face are reported from a study of 11 companies. Next, a best practice for managing risk in clinical trials will be described and discussed. The importance of metrics will also be described and best practices for establishing and using metrics in organizations. Finally, example uses of technology for managing risk in clinical trials will be shown.
The following topics in Clinical Development & Risk Management will be discussed:
1) Survey on Risk Dimensions in Clinical Development
- Background to the survey
- Dimensions of Risk Identified
Results, Safety, Efficacy, Recruitment, Timelines (other than recruitment), Budgets, Resources, Systems
- Summary
2) Processes for Managing Risk – A Best Practice
- Process Overview
- Basic Tools
- The Study Plan
* Project/Study Risks: Examples
* Study Status Review Meeting
* Tracking Tools
- Getting a Plan Pre-Approved
- Linking Team Members
- Summary: Managing a Trial is Managing Risks
3) Managing Risk with Metrics
- Approach to Developing Metrics
- Clinical Milestones and Deliverables
- Clinical Milestones and Metrics Used by Life Science and Academic Institutions
4) Example uses of Technology
5) Summary and Conclusions
WORKSHOPS
* Electronic Laboratory Notebook Workshops – Rescentris, Symyx
* Applying Roadmap processes to the Clinical Trials Project Process, Joel Hoffman (Insightful)
* Innovation Management in R&D – an Enterprizer Briefing and Case Study, Joseph Bitran (Enterprizer)
* Using Interactive Visual Analytics to Accelerate Drug Development, David Mosenkis (Spotfire)
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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