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ADVANCING DRUG SEARCH
WITH POSTGRESQL AND
AZURE AI
Taras Kloba
Senior Solutions Architect, Data & AI at
Microsoft
POSETTE - 2024
PANACEA
Taras Kloba
Senior Solutions Architect, Data & AI at Microsoft
• Founded a volunteering IT group for Ukrainian army
systems, winner of the TIDE NATO Hackathon and
Ukraine Defence Hackathon.
• Co-leader of PostgreSQL Ukraine and Big Data
Community
• More than 14 years of experience in Data
Engineering
• Ph.D. in Economics
• Winner of the Ukrainian IT Awards 2019 in Software
Architecture
• Certified Cloud Architect & Data Engineer on Google
Cloud, Microsoft, and Amazon Web Services.
Microsoft Certified Trainer
• Father of three daughters
PANACEA
the challenge.
understanding our challenge
3
PANACEA
Medication Match-Up.
When a new war starts, NATO troops
from different countries unite, each
with their medical supplies. Our
challenge was to make an app that
helps find the same medicine
across different country brands.
4
The Suwalki Gap: A Hypothetical Flashpoint
PANACEA
PANACEA
the solution.
innovation born of necessity
5
PANACEA
Inna Olkhova.
The diagram shows our app's ability to
match different medicine brands
through their active ingredient,
Acetaminophen. Inna’s idea helps find
the same medicine, whether it's Tylenol
in the US, Panadol in the UK,
Paracetamol in the EU, or Dafalgan in
France.
known as the "Bee Paramedic"
6
PANACEA
Tata Kepler.
From Artistry to Aid: Shaping Accessible Care in the
Field
7
Tata showed us how medicine sorting works,
especially when volunteers might not know medical
terms. She introduced us to using the ATC system in
our app, making it easier for everyone to find and
organize medicines correctly.
PANACEA
Daryna Smolnikova.
Daryna shared the idea of using NFC,
QR codes, and short links to store and
share information about the wounded.
She emphasized that sometimes,
sharing this information, even with the
enemy, is crucial to saving lives.
Immediate Action: Key to Battlefield Survival
8
PANACEA
Iryna Soloshenko.
Train Evacuations in Ukraine: Pioneering Lifesaving
Journeys
9
PANACEA
tech
specs.
engineering precision for lifesaving solutions
10
PANACEA 11
Architecture.
Azure Database
for PostgreSQL
with the Azure_AI
extension
PANACEA 12
Architecture.
Azure Database
for PostgreSQL
with the Azure_AI
extension
Can be replaced
with
azure_local_ai
extension
Can be replaced
with
Data API Builder
PANACEA 13
ILIKE.
The ILIKE operator in PostgreSQL is used for
case-insensitive pattern matching. It
functions similarly to the LIKE operator but
ignores the case of the character
SELECT *
FROM drugs
WHERE drug_name ILIKE
'tylen%';
SELECT *
FROM drugs
WHERE drug_name ILIKE
'%tylen%';
PANACEA 14
TRIGRAMS.
A trigram is a group of three consecutive
characters in a string. By comparing these
trigrams, PostgreSQL can measure the
similarity between strings. Useful for finding
similar strings despite minor spelling errors
and variations.
CREATE EXTENSION pg_trgm;
SELECT drug_name
FROM drugs
WHERE drug_name % 'tylelon'
ORDER BY similarity(drug_name, 'tylelon')
DESC;
PANACEA 15
VECTOR SEARCH.
Vector search uses vector representations of text to
find similar items. By comparing these vectors,
PostgreSQL can measure the similarity between text
descriptions.
CREATE EXTENSION azure_ai;
ALTER TABLE drugs
ADD COLUMN vector VECTOR GENERATED ALWAYS AS
(azure_ai.vectorize(drug_name)) STORED;
SELECT drug_name
FROM drugs
ORDER BY vector <=> azure_ai.vectorize('pill for
pain management')
LIMIT 5;
PANACEA 16
VECTOR SEARCH.
Vector search uses vector representations of text to
find similar items. By comparing these vectors,
PostgreSQL can measure the similarity between text
descriptions.
CREATE EXTENSION azure_ai;
ALTER TABLE drugs
ADD COLUMN vector VECTOR GENERATED ALWAYS AS
(azure_ai.vectorize(drug_name)) STORED;
SELECT drug_name
FROM drugs
ORDER BY vector <=> azure_ai.vectorize('red pill for
headaches')
LIMIT 5;
PANACEA 17
DRUGGPT (AI RAG ASSSISTANT).
RAG (Retrieval-Augmented Generation) is a hybrid
approach that combines retrieval and generation
techniques to enhance the quality of AI responses. It
first retrieves relevant information from a knowledge
base or database and then uses this information to
generate more accurate and contextually relevant
answers.
PANACEA 18
Search.
Layer 1 Layer 2 Layer 3 Layer 4 Layer 5 Layer 6 Layer 7
Machine learning models
for semantic
representation, ranking
for the rest of results.
Exact and pattern text
search (ilike%), trigram
similarity calculation,
and ranking for best
results.
Similarity search with
threshold 0.7, ranking for
best results.
Machine learning models
for semantic
representation, with a
threshold of 0.9, ranking
for best results.
Pattern text search
(%ilike%), trigram
similarity calculation,
ranking for best results.
Full-text search in
summary, description, and
indication columns.
Similarity search with
threshold 0.5, ranking for
best results.
Yes
No
Is result
found?
Yes
No
Is result
found?
Yes
No
Is result
found?
Yes
No
Is result
found?
Yes
No
Is result
found?
Yes
Is result
found?
No
PANACEA 19
OCR Search.
[Tylenol], [Acetaminophen], [Pain], [Reliever],
[Fever], [Reducer], [Extra], [Strength], [FOR],
[ADULTS], [500], [mg], [each]
Database
PANACEA 20
Knowledge Graph.
Powered by DrugBank.com database
PANACEA
demo.
21
PANACEA
try it out.
22
PANACEA
get in touch.
Taras Kloba
aka.ms/taras
23

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"NATO Hackathon Winner: AI-Powered Drug Search", Taras Kloba

  • 1. ADVANCING DRUG SEARCH WITH POSTGRESQL AND AZURE AI Taras Kloba Senior Solutions Architect, Data & AI at Microsoft POSETTE - 2024
  • 2. PANACEA Taras Kloba Senior Solutions Architect, Data & AI at Microsoft • Founded a volunteering IT group for Ukrainian army systems, winner of the TIDE NATO Hackathon and Ukraine Defence Hackathon. • Co-leader of PostgreSQL Ukraine and Big Data Community • More than 14 years of experience in Data Engineering • Ph.D. in Economics • Winner of the Ukrainian IT Awards 2019 in Software Architecture • Certified Cloud Architect & Data Engineer on Google Cloud, Microsoft, and Amazon Web Services. Microsoft Certified Trainer • Father of three daughters
  • 4. PANACEA Medication Match-Up. When a new war starts, NATO troops from different countries unite, each with their medical supplies. Our challenge was to make an app that helps find the same medicine across different country brands. 4 The Suwalki Gap: A Hypothetical Flashpoint PANACEA
  • 6. PANACEA Inna Olkhova. The diagram shows our app's ability to match different medicine brands through their active ingredient, Acetaminophen. Inna’s idea helps find the same medicine, whether it's Tylenol in the US, Panadol in the UK, Paracetamol in the EU, or Dafalgan in France. known as the "Bee Paramedic" 6
  • 7. PANACEA Tata Kepler. From Artistry to Aid: Shaping Accessible Care in the Field 7 Tata showed us how medicine sorting works, especially when volunteers might not know medical terms. She introduced us to using the ATC system in our app, making it easier for everyone to find and organize medicines correctly.
  • 8. PANACEA Daryna Smolnikova. Daryna shared the idea of using NFC, QR codes, and short links to store and share information about the wounded. She emphasized that sometimes, sharing this information, even with the enemy, is crucial to saving lives. Immediate Action: Key to Battlefield Survival 8
  • 9. PANACEA Iryna Soloshenko. Train Evacuations in Ukraine: Pioneering Lifesaving Journeys 9
  • 11. PANACEA 11 Architecture. Azure Database for PostgreSQL with the Azure_AI extension
  • 12. PANACEA 12 Architecture. Azure Database for PostgreSQL with the Azure_AI extension Can be replaced with azure_local_ai extension Can be replaced with Data API Builder
  • 13. PANACEA 13 ILIKE. The ILIKE operator in PostgreSQL is used for case-insensitive pattern matching. It functions similarly to the LIKE operator but ignores the case of the character SELECT * FROM drugs WHERE drug_name ILIKE 'tylen%'; SELECT * FROM drugs WHERE drug_name ILIKE '%tylen%';
  • 14. PANACEA 14 TRIGRAMS. A trigram is a group of three consecutive characters in a string. By comparing these trigrams, PostgreSQL can measure the similarity between strings. Useful for finding similar strings despite minor spelling errors and variations. CREATE EXTENSION pg_trgm; SELECT drug_name FROM drugs WHERE drug_name % 'tylelon' ORDER BY similarity(drug_name, 'tylelon') DESC;
  • 15. PANACEA 15 VECTOR SEARCH. Vector search uses vector representations of text to find similar items. By comparing these vectors, PostgreSQL can measure the similarity between text descriptions. CREATE EXTENSION azure_ai; ALTER TABLE drugs ADD COLUMN vector VECTOR GENERATED ALWAYS AS (azure_ai.vectorize(drug_name)) STORED; SELECT drug_name FROM drugs ORDER BY vector <=> azure_ai.vectorize('pill for pain management') LIMIT 5;
  • 16. PANACEA 16 VECTOR SEARCH. Vector search uses vector representations of text to find similar items. By comparing these vectors, PostgreSQL can measure the similarity between text descriptions. CREATE EXTENSION azure_ai; ALTER TABLE drugs ADD COLUMN vector VECTOR GENERATED ALWAYS AS (azure_ai.vectorize(drug_name)) STORED; SELECT drug_name FROM drugs ORDER BY vector <=> azure_ai.vectorize('red pill for headaches') LIMIT 5;
  • 17. PANACEA 17 DRUGGPT (AI RAG ASSSISTANT). RAG (Retrieval-Augmented Generation) is a hybrid approach that combines retrieval and generation techniques to enhance the quality of AI responses. It first retrieves relevant information from a knowledge base or database and then uses this information to generate more accurate and contextually relevant answers.
  • 18. PANACEA 18 Search. Layer 1 Layer 2 Layer 3 Layer 4 Layer 5 Layer 6 Layer 7 Machine learning models for semantic representation, ranking for the rest of results. Exact and pattern text search (ilike%), trigram similarity calculation, and ranking for best results. Similarity search with threshold 0.7, ranking for best results. Machine learning models for semantic representation, with a threshold of 0.9, ranking for best results. Pattern text search (%ilike%), trigram similarity calculation, ranking for best results. Full-text search in summary, description, and indication columns. Similarity search with threshold 0.5, ranking for best results. Yes No Is result found? Yes No Is result found? Yes No Is result found? Yes No Is result found? Yes No Is result found? Yes Is result found? No
  • 19. PANACEA 19 OCR Search. [Tylenol], [Acetaminophen], [Pain], [Reliever], [Fever], [Reducer], [Extra], [Strength], [FOR], [ADULTS], [500], [mg], [each] Database
  • 20. PANACEA 20 Knowledge Graph. Powered by DrugBank.com database
  • 23. PANACEA get in touch. Taras Kloba aka.ms/taras 23