Oncocross

AI DrugDrug development

Oncocross is an Artificial Intelligence-based pharmaceutical company specializing in drug discovery/cancer drug development.

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Highlights
Company Overview
Problem Overview
Solution Overview
Business Model
Competitive Landscape
Founders' Bio

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Highlights

AI based biotech company specializing in drug development with patented AI algorithm
Mitigate drug development risk by saving upto 8 years and 95% of the cost
First AI biotech in Korea to L/O drug candidate to a traditional pharmaceutical company
Proprietary database set of 100,000+ patients transcriptomic data, 400+ disease signature data, 19+ cohorts of rare disease data, 25,000+ drug signature data, 40 main types of cancer with 79 subtypes
16 pipelines and 5 will begin clinical trials within 12-month
Collaborating with 60+ big pharmas, research institutes, universities, and hospitals
Raised KRW16.5bn (USD14mn, 140% of targeted amount) in Series B funding this August

Company Overview

Oncocross is an Artificial Intelligence based biotech specializing in drug development.

Oncocross’ service is based on the two AI platform described below:

ONCO AI – is an AI platform to screen optimal indications for drug compound in preclinical or clinical stages and to find the most suitable combination drugs to develop Incrementally Modified Drug (IMD) or orphan drugs, using proprietary human transcriptomic data (RNA expression), disease data, and drug data. Using ONCO AI, we can accelerate drug development process in a shorter time at a lower cost.

ONCOfind AI – is an AI platform to screen and identify the most suitable biomarker for anti-cancer drug compound candidate using proprietary standardized human transcriptomic data of multiple races and various phenotype information of cancer. This platform can also identity the original anatomic site of primary cancer tumor for Carcinoma of Unknown Primary (CUP).

Problem Overview

We believe many drugs fail clinical trials because most of the diseases including cancers are caused by complex interactions between many genes. However, the majority of pharmaceutical companies focus on a single target using one or two drugs. Therefore, we think the focus on a single target is insufficient to treat diseases. Instead, Oncocross approaches with the focus on gene expression pattern.

Solution Overview

Extended Profile

JPI-289. Early this year, we L/I a lead compound JPI-289 from Jeil Pharma to screen additional indication. Jeil is developing JPI-289 as treatment for stroke and we screened to find that it can also be used to treat NASH as well. Currently we are validating in animal model and we expect to begin clinical trials in 2H of next year. Jeil Pharma was able to add one more pipeline while saving both time and huge amount of money. (Rev. will be milestone fees and L/O in the later stage)

Cancer Biomarker

In cancer, we recently completed service agreement with ST Pharm to screen to find optimal biomarker for their new anti-cancer drug candidate. They have adjusted clinical trial design based on our result and will start clinical trials in 2H of this year. ST Pharm was able to increase the success rate of clinical trials with minimum cost.

Incrementally Modified Drug (IMD)

In IMD, we screened from our drug database that OC-501+504 combo shows a good indication for sarcopenia. After validating with animal model internally, in June this year, we L/O to Korea Pharma. This records the first L/O deal not only Korea, but also in APAC region of any AI drug discovery/development company to a traditional pharmaceutical company. Korea Pharma will conduct clinical studies soon, and this was done without spending millions of dollars in many years. (Rev. is upfront fee, milestone fees, royalty fees)

Orphan Drug

In orphan disease, It is estimated that there are 7,000 rare diseases worldwide with more than 350 million patients affected and less than 6% of the diseases have approved treatments. Through ONCO AI, we can screen and repurpose existing drugs with known pharmacokinetics and pharmacodynamics to find the solution for rare disease with unmet medical needs. Using this approach, we have selected a good candidate drug for Amyotrophic lateral sclerosis (ALS) or also known as Lou Gehrig’s diseases. Currently, we are in process of licensing agreement activities and at the same time, we are planning a Phase II clinical trials early next year.

Rescue Drug

In rescue drug, we received 5 compounds that have failed in clinical trials from Boehringer Ingelheim, a German multinational pharma. Out of 5, we found 1 compound showing a reasonable indication and we are in the animal testing. We are discussing with BI at the same time on the next step forward.

Go-to-Market Strategy and Business Model

Revenue model
- License-Out
  - upfront fee
  - milestone fees: enter clinical studies, IND submission, FDA approval
  - royalty: when the drug is sold to market

- Co-develop and share milestone fee
- Service fee
  - find the optimal biomarker for anti-cancer drug compound

Pricing
- - L/O depends on the type of disease, clinical trial phase
  - orphan drug prices are very high

Sales and distribution model
- - business development team: 2 domestic, 2 US, 1 China

Customer pipeline list
- - Novo Nordisk, Boehringer Ingelheim, ST Pharm, Korea Pharma, Daewoong Pharmaceutical

Competitive Landscape

Market size:

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Resue Drug

on average approximately 4,500 drugs and medical devices are pulled from the market each year in the U.S.
only 14% of all drugs in clinical trials eventually win FDA approval according to new MIT study.
assuming average USD2.6bn spent for one approval, USD2.23bn are sunk cost.

Competition:

Oncocross AI platform is powered by the proprietary data set – homo sapiens’ transcriptomic data, drug data, disease data and patented AI algorithm ‘ReDRUG’ to screen and match drug and disease.

Founders' Bio

Yirang Kim

CEO

- Ph.D., Medical Science, KAIST - Medical Oncologist (Hematology), - Asan Hospital, Internal Medicine, Department of Oncology, -Visiting Scholar, Wellman Center for Photomedicine, Harvard Medical School, - Visiting Scholar, MIPS (Molecular Imaging Program at Stanford), School of Medicine, Stanford University"