For enhanced accuracy in diagnosis and treatment response assessments to contribute
to improved treatment rate and reduction of late complications
Tokyo, Japan ― March 31 , 2021 － LPIXEL Inc., a leader in image analysis and processing in life science and medical research, announced the commencement of joint research into a childhood leukemia diagnostic support system using AI with the National Center for Child Health and Development (“NCCHD”).
This project aims to develop and build a diagnostic support system for childhood leukemia by applying technologies garnered through the development of medical and drug discovery AIs to the diagnostic information collected by the NCCHD and other joint research facilities, etc. through their clinical studies.
This diagnostic support system will identify the characteristics of blood cells in bone marrow smear preparations, which are used for the diagnosis of childhood leukemia. The ability to identify characteristics that cannot be observed with the human eye enables more accurate diagnoses and treatment response assessment, which can further contribute to a higher cure rate and a reduced rate of leukemia recurrence.
Background of research
Childhood leukemia is a type of blood cancer. It is the most common pediatric cancer, with about 700 to 800 children being diagnosed with childhood leukemia every year. The recent advancements in therapeutic drugs and treatment for childhood leukemia has led to improved treatment outcomes such as a five-year survival rate of over 80%. On the other hand, the cure rate still leaves room for improvement, and the importance of alleviating long-term complications remains of interest.
To answer these needs, it is critical to more accurately assess the leukemia classification and treatment response to enable the selection of the best treatment approach for each patient.
● Reduce the burden on diagnosticians
Blood cancers, including childhood leukemia, are diagnosed using bone marrow smear preparations. While the preparations are examined under a microscope by the human eye, diagnosis of cancer requires advanced knowledge and experience. The quantification and streamlining of this examination is expected to reduce the burden on diagnosticians.
● Establish a more effective leukemia classification system
In conventional bone marrow smear observation, the leukemia is classified through a combination of a morphological classification by a specialist and other tests in order to decide the treatment strategy. It is expected that replacing these examinations with an AI diagnostic support system can achieve classifications beyond what conventional visual observations can detect. Higher-accuracy classification paves the way for better treatment selection and leads to both further improvement in cure rate and reduction of late complications.
 National Center for Child Health and Development
 Foundation for Promotion of Cancer research
AI for Accelerating Pharma R&D
The utilization of AI is becoming increasingly common in the development of drugs in the pharmaceutical industry. The application of AI to the drug discovery process makes possible not only a quantitative evaluation ability and performance equivalent to human perception, but also an enhancement of the effectiveness of the measurements made that is brought about by being able to execute tasks on a scale that is beyond human capacity. LPIXEL has built up research achievements working together with Astellas Pharma, Takeda Pharmaceutical Company, and other leading pharmaceutical companies.
LPIXEL’s professional team offers one-stop support for your needs in all stages of the drug discovery process with proposals covering everything from experimental designs to optimal data acquisition and collection methods for AI learning.
IMACEL product site: https://imacel.net
LPIXEL is a leader in advanced image analysis and processing technology encompassing the life science field. Founded in March 2014, LPIXEL is dedicated to offering research facilities, top-tier image analysis technologies and medical diagnosis technologies, both of which adopt advanced AI technology. LPIXEL revolves around business such as its medical image analysis software, “EIRL,” and its AI-based image analysis service, “IMACEL.”
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