I’m sitting in the Basic Science Research Building Auditorium listening to a presentation by Franklyn G. Prendergast, MD, PhD, the keynote speaker for the NCIBI annual meeting.
I’m using this as an experiment – I’m blogging Dr Prendergast live to see how I manage it and how it works for me. This is live and therefore by its nature imperfect; this should be considered a sharing of my notes and not a transcription of remarks or meaning. Any errors are mine and not the speaker’s.
Topic: Designing for Individualized Medicine
Setting objectives at start of program for any and all diseases
Research objectives:
epidemiology, etiology, progression
Clinical objectives:
to prevent or predict disease
Absolute prevention not possible but can mitigate risk
design effective interventions
Education objectives:
piblic and professional, at all levels
importance of understanding statistics
Need to understand population characteristics in order to understand individual variations and their consequences
Where do we get population data? Clinical patient databases + biobanking placed in integrated database of controls and disease states
Informatics and computational biology
Ultimate outcome is improved quality of life and/or cure of disease
inter-disciplinary and collaborative approach required – look at both basic sci and clinical findings to understand individual in context
Center for Individ Med (CIM) – each one different depending on institution and population
Redefine Disease Risk/Prevention
using Biomarkers
modified by environment, infections, behaviors, nutrition, genomics, toxins
Can’t answer individual questions of risk/prognosis with population stats
CIM Tech support:
Need huge computational clusters to analyze the data
Need huge data sets – genomics – with types of data integrated
Biomedical Informatics and Systems Biology huge domains – need community not just a department working on this
Discovery and Development Program steps
Biomarker Discovery
Biomarker Assay
Assay validation
Diagnostic validation
Launch (Kits, instruments, reimbursement, etc)
Need to be very sure of results esp in the press or will confuse the public
Is IM hype?
no, it’s what medicine has always wanted to be
Do we really need all this data and infrastructure?
Role of informatics is to simplify – need to cluster data in a way that makes sense – but for now, need all the data before we can build accurate clusters
What is the role of biomedical informatics?
This is very complex data – highly networked
role of informatics is to standardize formats for data
also, pattern recognition; define accuracy; validation
Idiosyncratic nature of medical institutions works against national EHR
** Have to convince clinicians and patients that the info presented is real and valid and can be relied on/acted on **
Where do we start?
Already started – NCIBI good example
What are our societal responsibilities?
Science advances more rapidly than scientists can deal w/ the changes
Need to address societal issues
Simultaneously and in equal measure w/ scientific problems
cannot ignore privacy, ethics, morality
information has consequences in human behavior, e.g., genetic diagnosis of Huntington’s Chorea
At present 32 diseases associated with genetic snips
On one hand – allows intervention
Other hand – response of individual varies by age and environment
But – public wants the tests and is cynical ab out risk
And of course, who pays for all this?
How many tests do we need?
What level of certainty?
In conclusion:
Respect public concerns
Find effective results
Don’t announce to media until certain
Collaborate as much as possible
Think about pain management and other indirect disease mgt issues