Explainable Artificial Intelligence is HERE

SIMPLIFY
DRUG
DISCOVERY

CIMPLRX

Overview

Platforms Developed Before

UNC at Chapel Hill – Machine Learning Via Web Application
Bristol-Myers Squibb – Combinatorial Chemical Library Design / HTS Data Analysis & Visualization
Amgen – Discovery & Preclinical Data Analysis & Visualization
CHDI – Medicinal Chemistry CRO Management

NOW

CIMPLRX is discovering and developing new drug candidates
using its own Explainable Artificial Intelligence (XAI) platform, CEEK-CURE.

CIMPLRX CAN PROVIDE INSIGHTS INTO DRUG DISCOVERY

Concept of XAI

XAIAI

Hover your mouse pointer over the image to observe the difference.

Platform

CIMPLRX XAI PLATFORM

Target Based Hit Identification

A Uniprot ID is used to collect known compounds associated with the target and perform supervised and unsupervised learning. Generated models are used to design new compounds and screen commercial databases automatically.

Input: UniProt ID
Design new compounds and screen commercial libraries
Screen compounds in public databases
Generate directional models
Design new compounds and screen commercial libraries
Collect known relationships and build machine learning models

Compound based Hit Identification

Seed compounds are used to define the biological spaces and collect known relationships between compounds and targets. Generated models are used to design new compounds and screen commercial databases automatically.

Input: Seed Compounds
Collect data using 6 different chemical spaces
Build machine learning models, make predictions, and design new compounds automatically
Build directional models, make predictions, and design new compounds automatically

Lead Optimization

Prebuilt models are available to make predictions, and the results can be used to filter compounds.  The color and size of circles shown on each structure are used to explain relative importance.  Green and red colors indicate positive and negative contributions, respectively.  The size of circles represents the strength of each contribution.

Color contributions
Filter results

moa identification

Active compounds are used to collect known compound-target relationships which are then turned into multiple predictive models.  Top 3 targets per each compound and the occurrence of each target are shown.

Input: active compounds
Model generation and make predictions
Identify top 3 targets per each input compound and calculate their frequencies
Make comparisons between input compounds and compounds found in the training set

Explainable AI (XAI) Platform, CEEK-CURE

Explain Models

CEEK-CURE allows users to choose models and make predictions on a dataset of drugs. Results are shown with colored structures, prediction values, and standard deviations. Users can also combine different models for easy analysis.

Explain Results

CEEK-CURE provides various tools to explain results, including parallel coordinates, chord diagrams, dendrograms, heatmaps, interactive scatter plots, and clustering and diversity tools for structure-activity relationship analysis.

Explain Processes

CEEK-CURE displays the drug development process as a graph, allowing users to find related information through protein nodes or keyword searches. Active sites, compounds, and interaction information can be accessed from the Uniprot website. PyMOL can be used to view the protein’s active site, and protein structures, compounds, and data are automatically linked.

And Share

History

– 2 Government R&D Grants
 (Government Ministry of Health and Welfare & Ministry of Science and ICT / Ministry of Food and Drug Safety)

Series B Funding
 (KRW 5.5BN (≈USD 5M))

– 1 Government R&D Grant
 (Korea Drug Development Fund, KDDF)

– Government R&D Grant
 (AI-Based Innovative New Drug Discovery)

– 3 Projects with Pharma
 (Dongwha / Shin Poong / Samjin)

– 2 Projects with Biotech
 (Baobab AiBIO / eFlask)

– Moved into MUNJEONG, SEOUL

– Internal Wet Lab (Biology/Chemistry) Established

– 2 Projects with Pharma
 (Dong-A ST / SK Chemicals)

– 1 Project with Biotech (Curex)

Series A Funding
 (KRW 5BN (≈USD 4.4M))

– 2 Government R&D Grants
 (AI Drug Discovery Platform)

– Ulsan Univ. Project 

– Moved into AI YANGJAE HUB, SEOUL

 CIMPLRX
CIMPLRX CO., LTD. Established

Our Partners

University

Biotech & Pharmaceutical Companies

Baobab_AIBIO

Investment Institutions

Aventures
BNK_VC
CompanyK

Business Model

contact

02-6427-3100 / info@cimplrx.com
8F, AJ Building, 9, Jeongui-ro 8-gil,
Songpa-gu, Seoul, Korea

CIMPLRX

about us

CIMPLRX is discovering and developing new drug candidates using its own Explainable Artificial Intelligence (XAI) platform, CEEK-CURE.  Create ExplainablE Knowledge (CEEK) is the user interface portion of the platform designed to analyze and visualize results and capture the discovery process. Collect and Uncover RElationships (CURE) is our XAI engine which resides on the server side and handles various requests made from CEEK.