AILANI is a novel and unique semantic search enterprise solution for fast, easy and comprehensive knowledge discovery. It combines semantic modelling, ontologies, linguistics and artificial intelligence (AI) algorithms in a self-refining system that delivers results based on inter-related meaning of facts. AILANI not just allows for phrase searches as well as structured queries, it offers its users a unique hybrid natural language question answering system combining machine learning algorithms with semantic network-based "prior knowledge" inference. It integrates seamlessly with existing infrastructure and helps leverage knowledge buried both in decade old data as well as data derived from news feeds and clinical trials providing real-time semantic analysis of breaking news. For the pharmaceutical industry it is critical to stay up to date with the latest clinical trials news for decision-making in drug development. Integration of the relevant data and using ontology-based refiners enables fast and efficient retrieval of information about the clinical competitive landscape.

1. www.biomax.com
AILANI
Artificial Intelligence LANguage Interface
AILANI for Clinical Competitive Landscaping
Angela
Angela Bauch (Assistant Director Product Management)
Biomax Informatics AG
4.10.2021 AI-SDV

2. AILANI: Semantic Integration & Search Solution
Discovery of Tacit Corporate Knowledge
Answers of Research Questions
Actionable Insights on Key Business
Questions

3. AILANI publicly accessible
https://ailani.ai

4. Keyword results
Benefit from AI and Natural Language Processing
AI suggestions
AI answers
Search journey with smart
breadcrumbs
Drill-down relevant results based
on public/proprietary data
Results panel
Infobox with context information based
on public and proprietary data

5. Semantic Search Results
combining:
- Results from natural language queries
Machine learning system
-Results matching with „beliefs“
NLP query parser
- Results on scientific concepts and
subsequent manual filtering
Artificial Intelligence (AI) with AILANI
Semantic Objects
(Growing Meta Ontology /
Semantic Network)
tagging
indexing
NLP Algorithms
Beliefs
(Triples + Evidence)
Global Search
Additional
specialized Searches
Spezialized
data detectors
OCR, OSR,
pattern detectors
Inhouse Documents
News Archive
Unstructured data
Chemical Search
Public / Proprietary
Data Resources
Structured data
Semantic Core

6. Content Sources of AILANI for Free
Literature
• Medline abstracts
• PubMedCentral articles
• ClinicalTrials.gov
• COVID-19 lit
(Elsevier, medRxiv, bioRxiv)
• Newsfeeds
(WHO, FDA, FoodNav...)
• COVID-19 patents
• Selected science-related
Wikipedia articles
• Extendable by proprietary
documents
(Word, Powerpoint, ELN)
Databases
• 70 public databases
(UniProtKB, PubChem,
ChEMBL, DrugBank, PDB,
ICD-10, dbSNP…)
• Extendable by proprietary
structured data
(from antibody inventory to
chemical library and IP port-
folio)
Ontologies
• 120 life science ontologies
(Disease, GO, NCBITax,
ChEBI, FMA, HP…)
• Extendable by proprietary
ontologies

7. The AILANI Knowledge Graph
AILANI starter
knowledge base has
~44 million triples
Customer
implementation
typically handles > 400
million triples

8. The Question Answering Index: Semantic Networks & Neural Networks
The AILANI „Hybrid“ AI:
Prior Knowledge,
Reasoning and
Generalization + neural
networks for
bootstrapping a
"deeper understanding“
AI: Finding yet
unknown concepts...

9. Semantic Search Algorithms — NLP Question Answering
> NLP Parser — The grammatical
structure of an entered natural
language question is analyzed
> Triple Search — The entered question
is translated into a query against all
previously extracted beliefs (triples)
> Answer Generator — The objects of
interest encoded in the result triples are
reported, including their original source

10. Semantic Search Algorithms — AI Question Answering
> From all documents, a candidate set of 4-sentence
chunks is determined, which likely contain possible
answers.
> The candidate set is generated using the semantic
tagging index, using ontologies for contextualization.
Therefore, the quality of the ontologies has a certain
influence on the final answer generated by the AI
models.
> From the candidate set of 4-sentence chunks, a neural
network extracts direct answers to the entered
question.
> Based on the ML score, the answers are reported in
ranked order

11. Ask AILANI...
What increases the temperature leading to superconducting?
How much CO2 is released into the atmosphere?
What is a Bcr Abl inhibitor?
What is the Mooney viscosity of butadiene styrene rubber?
How does SARS compare to MERS?
Who won the nobel prize in economics?
How to treat schizophrenia?
What gene is associated with speech?
What are efficient organocatalysts?
Which KRAS covalent inhibitors are being tested in the clinic?

12. Which KRAS covalent inhibitors are being tested in the clinic?

13. AILANI for competitive landscaping
Find and filter targets,
drugs or clinical data
to identify market
trends
Sophisticated concept
search using ontology-
based refiners for
diseases, compounds or
organizations
Access to integrated
linked data, such as
gene, protein,
compound or 3D
structure reports

14. Use Case: RAS, drugging the undruggable
>Mutations in KRAS are reponsible for one third
of all cancers
>Questions:
> Which companies conduct clinical studies with KRAS?
> Which institutes work on RAS isoform mutations in a
tumour type of interest, e.g. pancreatic adenocarcinoma?
> What is known about KRAS at the gene, protein or
protein structure level?

15. Dynamic overview of companies conducting KRAS studies

16. Search and find companies of interest

17. Access to integrated protein, cmpd & 3D-structure reports
Tipifarnib

18. AILANI for KOL identification
Identify expert
relevant to a research
topic, therapy area,
disease or treatment
Option to refine results
for additional expertise,
publication activity or no.
of publications
Explore and identify
potential
collaborators using
the interactive social
graph

19. Challenge: Elucidation of MoA of a ligand
Identification of a ligand with the desired effect,
but what is the receptor?

20. Task: Find technologies empowering surfaceome research

21. AILANI KOL identification

22. AILANI Social Graph

23. The AILANI social graph allows
you to identify experts relevant
to a research topic, therapy
area, disease or treatment

24. AILANI – Advantages at a glance
> Access all internal and external data and
information at one single point – AILANI integrates
all structured and unstructured date regardless of
origin, location and date
> Transfer knowledge efficiently within your
organization – Speed-up your product life cycle by
facilitating access to key information
> Keep the know-how in your company, even if a
knowledge carrier leaves your company – Save
and maintain all knowledge in one single place
> Provide powerful information resources at your
fingertips – Wherever you are, access AILANI
through user-friendly Apps for all mobile devices
> Profit from a simple and attractive User
Experience – AILANI makes search simple and
delivers most relevant answers regardless of the
quality of the original search term
> Personalized User Interface – Target different user-
groups with specialized AILANI “Personas”
> Accelerate your innovation cycles and gain an
edge over your competitors (Competitive
landscaping & KOL identification – Be an early-
adopter and profit from the large number of open
access semantic resources, while saving time and
money.

25. www.biomax.com
Thank you!