Leukemia is a non-solid tumor type of blood, bone marrow and lymphatic system, also known as "blood cancer", divided into two major types of acute leukemia and chronic leukemia, the cause is unknown. In 2000, there were 250,000 adults and children worldwide, of whom 210,000 died of illness. The lady in the world famous science home died of leukemia. In 2012, researchers at the Ohio State University published a paper in the "Cell" publication "Cell Cancer", which revealed for the first time how interleukin-15 induces large-granular lymphocytic leukemia, and the molecular pathway gradually uncovers blood cancer that has long been confusing for humans. mystery of.
However, leukemia is divided into dozens of types, and the number of clinical drugs is increasing. How to accurately classify? How to guide clinical medication? In order to solve these problems, the arrival of the personalized medical era is inevitable. The development of each era has gone through thousands of years. In today's technologically advanced, what are the enormous challenges facing the development of personalized medicine? At the 2015 China Medical Device Summit, Dr. Shi Chenyang, President of Kaijie, Asia Pacific, gave a wonderful speech on technology, policy and business model.
Personalized medicine = better efficacy + better use of medical resources
Personalized medical care is an inevitable outcome of the development of the medical profession. It is well known that each drug is not necessarily effective for the patient used, and the drug effects of diseases in different fields are also inconsistent. Dr. Shi Chenyang summarized the efficacy of several diseases at the meeting. As shown in the above table, some drugs are very ineffective for patients, such as tumors. Tumors are a very large class of diseases, one of the most globally ill diseases, but one of the least effective diseases. On average, a tumor drug is only effective in one quarter of patients. Therefore, the biggest vision of personalized medicine is to screen the treatment of cancer patients by means of diagnosis (molecular diagnosis or genetic diagnosis), that is, to select patients who are effective for the treatment before treatment, thereby optimizing the treatment efficiency. From the perspective of social resources, resource utilization can be optimized.
The huge challenge of personalized medicine
(i) Technology: standardized patient sample processing and testing processes - quality control standards for biological sample banks and shareable databases
Personalized medicine begins with a sample. Traditional diagnosis lacks attention to the sample, and its focus is on sensitivity, while personalized diagnosis and treatment are closely integrated. The focus is no longer on sensitivity, but on the discovery of disease to screening patients. The purpose of personalized medicine is to match the patient to the medication from the right medicine to the person.
The workflow is important for personalized medicine. Personalized medicine involves clinical medication, so the comparability of screening is very important. Standardized data sharing is very important, and standardization of technology platforms is very important. Peripheral blood DNA testing is a revolutionary advancement in personalized medicine, and technically it is primarily the detection of free DNA.
Liquid biopsy has a very high clinical value for both patients, doctors and hematologists/pathologists. For patients, liquid biopsy is a non-invasive, safer, less painful means of testing, giving patients who do not have access to an organization the opportunity to receive effective treatment once more, and to better care for the patient. For doctors, liquid biopsy can be used to get a quicker picture of the patient's condition, to continuously test the effect, and to detect changes in the condition (resistance or tumor recurrence). For hematologists/pathologists, liquid biopsies are faster than traditional tissue sampling and can be resampled, consistent with tumor tissue heterogeneity and blood consistency.
(2) Regulations/policies: clinical value is becoming more important – regulatory standardization will focus more on clinical validation than on analytical performance
Concomitant diagnosis and treatment are closely combined, and the value is not only in obtaining the diagnosis, but also in obtaining clinical value. As technology advances, the value of detection sensitivity or efficiency continues to decrease, gradually being replaced by clinical value. Clinical trials are increasingly important for the value of personalized medicine, and the clinical validation regulatory framework has a considerable impact on companion diagnostics.
Take the change in the US reimbursement system as an example. In the past, the companion diagnostic products of different technology platforms had no price difference in terms of payment, and can be used as long as it is approved by the FDA. Since 2 years ago, the US medical pricing system has given the Zcode standard: if the clinical diagnosis of the accompanying diagnosis is verified, then a Zcode is obtained, and after obtaining Zcode, it will receive twice as much. Zcode is only available when it is clinically combined with the corresponding medicine, so Zcode's acquisition is not so easy. This regulatory framework has prompted companion diagnostics and pharmaceutical companies to work together to develop personalized medicine. For example, in the United States and Europe, diagnostic companies must work with drug companies to develop companion diagnostics before they have access to Zcode. However, China does not currently have such a regulatory framework, but CFDA said that this is also China's future development direction.
(3) Application/Business Model: Bioinformatics - The greatest value of clinical applications
Today's second-generation sequencing brings revolutionary advances in personalized medicine. Domestic hospitals or research institutions spend a lot of money to buy sequencers. At present, 70% of the cost is in the sequencing step, but the difficulty and cost of sequencing will continue to decrease in the future, and data analysis will become the biggest bottleneck. Quest is the largest third-party testing company in the United States. There are currently twenty or thirty pathologists explaining the sequencing data and doing pathology reports. However, Quest believes that according to the growth of sequencing workload, they need at least 3,000 pathologists to analyze the data, which indicates that the clinical evaluation workload of gene sequencing results increases exponentially, and automated analysis of data is necessary, so automated analysis II Generation sequencing results are also an area of ​​great business opportunities.
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