Our inoculum effect manuscript in the journal Antimicrobial Agents and Chemotherapy highlighted in BIDMC news release.
"The Inoculum Effect in the Era of Multidrug Resistance: Minor Differences in Inoculum Have Dramatic Effect on Minimal Inhibitory Concentration Determination."
The manuscript describes use of D300-based inkjet printing technology to investigate the inoculum effect with a resolution not previously possible. The inoculum effect is the general observation that the minimal inhibitor concentration (in other words level of resistance) of an organism to an antibiotic increases when a higher density of organisms is tested. This is effect is especially prominent for beta-lactam antiibiotics. It is of potential clinical concern during some types of infections when the organism burden is high. Here we explored whether subtle differences in inoculum within the range allowed by current standards can effect the susceptibility testing results that clinical laboratories obtain and provide to clinicians. Our findings for organisms with certain types of multidrug-resistance and very important classes of antibiotics was that these small allowable differences in inoculum could change the MIC determinations and the determination of whether organisms were susceptible or resistant to the antibiotics tested.
Interview by science and technology writer, Marc Landas. "CONVERSATIONS WITH JAMES KIRBY: TRAINING AI FOR INFECTIOUS DISEASE DIAGNOSTICS"
KP Smith wins an "Outstanding Abstract Award" otherwise known as the OAA, for his experimental work on the inoculum effect.
The award description on the ASM Microbe 2018 awards website: "Sponsored by ASM and determined by the ASM Microbe Program Committee, these awards highlight outstanding abstracts presented by students, residents, or medical/clinical fellows. All abstracts submitted by the deadline will be considered for these awards. Awards will include a cash prize of $200."
Our Gram stain artificial intelligence platform was selected as a competitor in the 2018 Stat Madness Competition.
Work from our laboratory was selected as a competitor in the 2018 Stat Madness Competition. This bracket style national competition will allow voters to choose among important medical innovations developed at selected medical centers and universities across the United States. Our artificial intelligence-based-platform named Technologist Assist allows automatic imaging and interpretation of Gram stain results and ultimately will provide assisted laboratory diagnostic capabilities at near or remote sites.
Please vote for our work at the Stat Madness website: www.statnews.com/feature/stat-madness/bracket/
The laboratory has been fortunate to participate in Harvard Catalyst Reactor Program through the "Big Ideas, Small Features” Pilot Grant Award. A description of the program was recently published last week in Harvard Medical School news titled "Catalyzing Research Innovation."
A description of the supported work can be found at: "Reactor Program Awards Eight New Pilot Grants: Supports researchers with novel solutions to major clinical challenges."
New article published online today in Journal of Clinical Microbiology - Artificial intelligence, A New Tool for Interpretation of Bacterial Gram Stains
."Automated Interpretation of Blood Culture Gram Stains using a Deep Convolutional Neural Network" was published online today in the Journal of Clinical Microbiology. Congratulations to co-first authors: postdoctoral fellow, KP Smith, and medical microbiology fellow, Anthony Kang.
The article describes use of artificial intelligence in combination with a Metafer (MetaSystems) automated microscope to automatically interpret blood culture Gram stains without human intervention.
Link to Abstract.
Link to final accepted manuscript file.
Kirby Lab Blog