TW202242897A - Apparatus for treating mild cognitive impairment and dementia - Google Patents

Abstract

Methods and apparatuses are described herein for treating a patient with mild cognitive impairment (MCI) or dementia by one or more digital therapeutics. For example, a patient who has been diagnosed with the MCI or dementia may administer one or more digital therapeutics to the patient to improve a plurality of neurohumoral factors that cause the MCI or the dementia of the patient. The digital therapeutics may include one or more digital instructions that are generated to treat at least one imbalance of the plurality of neurohumoral factors based on at least one neurohumoral change among the plurality of neurohumoral factors by the patient's performance of the one or more digital instructions. The one or more digital instructions may include at least one of an execution environment setting, a lifestyle change, learning, exercising, or affirmation/achievement task.

Description

Devices and methods for treating mild cognitive impairment and dementia

The disclosed embodiments relate generally to digital therapeutics (DTx), and more specifically to amnestic mild cognitive impairment (mild cognitive impairment (MCI) and Alzheimer's disease, Developmental inhibition and treatment of AD).

Dementia refers to a clinical syndrome that prevents people from performing daily activities due to cognitive decline in memory, language, and judgment after birth. The types of dementia are divided into degenerative dementia (including Alzheimer's disease, vascular dementia caused by stroke, and those caused by various other factors such as injury or drugs. Currently, the US Food and Drug Administration (Food and Drug Administration, FDA) approved two types of Alzheimer's disease treatment drugs: cholinesterase inhibitors (such as Donepezil (Donepezil), Rivastigmine (Rivastigmine), and galantamine ( Galantamine)), and N-methyl-D-aspartate (NMDA) antagonists (such as memantine (Memantine)). However, the therapeutic effect of these drugs is very limited. Specifically, Said that the drugs mentioned above can only relieve the symptoms and cannot stop the development of the disease or cure the disease itself. In addition, the problem of the ineffectiveness of drug treatment for dementia has been raised, because drug treatment often bears serious and fatal side effects. Furthermore, The fact that there are so many interactions between drugs can be dangerous for patients taking such drugs.Therefore, there is a need to be able to treat or inhibit the progression of amnestic mild cognitive impairment and Alzheimer's disease without such limitations methods and equipment.

Methods and apparatus are described herein for treating patients with mild cognitive impairment or dementia with one or more digital therapies. For example, a medical professional (eg, a physician) can determine whether a patient has mild cognitive impairment or dementia based on one or more symptoms of mild cognitive impairment or dementia. If a patient has been diagnosed with mild cognitive impairment or dementia, a healthcare professional may prescribe and/or administer one or more digital therapies to the patient to improve the multiple conditions leading to mild cognitive impairment or dementia Neurohumoral factor. The one or more digital therapies include one or more digital instructions generated to induce neurofluid factors based on the patient's performance of the one or more digital instructions Changes in at least one of the neurofluid factors to treat an imbalance of at least one of the neurofluid factors. These nerve fluid factors may include sex steroid hormones, insulin-like growth factor-2 (insulin-like growth factor -2, IGF-2), β-catenin in Wnt signal transduction, Bcl-2 related anti-apoptotic genes 1 (Bcl-2-associated athanogene 1, BAG1), cyclic adenosine monophosphate response binding protein (cAMP response element-binding protein, CREB), multiple inflammatory factors, multiple corticosteroids, and multiple neurohormones at least A sort of. The at least one imbalance of the neurofluidic factors comprises sex steroid hormone imbalance, decreased IGF-2, β-catenin degradation, BAG1 inactivation, CREB inactivation, increased inflammatory factors, increased corticosteroids, and decreased neurohormones at least one. The one or more digital treatments are performed by the user's device.

According to "Year 2016 nationwide dementia epidemiology survey" (Report No.: NDR-1603-0015, June 2017, Central Dementia Center, Ministry of Health and Welfare, Korea), the standardized The prevalence rate of dementia (standardized dementia prevalence rate) is 8.18%, female is 10.46%, the total is 9.50%. The data show that the prevalence of females is higher than that of males.

To further specify the type of standardized dementia prevalence rate (9.50%) for Koreans over 65 years old, Alzheimer's disease accounted for 7.07% of the total, while vascular dementia accounted for 0.83% and others accounted for 1.60%. Obviously, compared with other types of dementia, Alzheimer's disease accounts for the vast majority (about 3/4).

Notably, standardized dementia prevalence increases as populations age. Comparing the standardized dementia prevalence rate for Koreans aged 65 and over to the standardized dementia prevalence rate for Koreans aged 85 and over, the ratio rose from 9.50% to 38.39%. In particular, the standardized prevalence of dementia rose to 53.99% in men over 85 years of age.

The standardized prevalence of dementia among the elderly in South Korea, and the estimated number of dementia patients in the future population based on age, sex, and region-standardized data from the 2015 census are particularly noteworthy. The standardized prevalence of dementia over age 65, which was 9.73% in 2016, is estimated to rise to 10.29% in 2020, 10.56% in 2030, and 16.09% in 2050. Based on changes in estimates, the number of dementia patients in South Korea will exceed 1 million in 2025 and 3 million in 2050.

Mild Cognitive Impairment (Korean Standard Classification of Diseases and Signs Code: F06.7), as an intermediate state between normal aging and dementia, does not cause any difficulty in daily activities, but Age group, can cause decline in memory and cognitive function. Types of mild cognitive impairment are divided into amnestic mild cognitive impairment, which suffers from memory loss, and non-amnestic mild cognitive impairment, which causes non-memory-related cognitive decline. As it is well known, about half of mild cognitive impairment develops into dementia, and mild cognitive impairment has attracted public attention in terms of preventing dementia.

According to the above-mentioned report, the standardized prevalence of mild cognitive impairment among Korean males over 65 years old is 18.09%, and that of females is 25.28%, for a total of 22.25%. The data showed that, as observed in the prevalence of dementia, the prevalence was higher among women than among men over the age of 65.

Further specifying the type of MDI in the standardized MDI prevalence rate (22.25%) for Koreans over 65 years old, amnestic MDI accounts for 16.69% and non-amnestic MCI accounts for 5.56% . Amnestic mild cognitive impairment accounts for about 3/4 of the total. Amnestic mild cognitive impairment in particular requires more aggressive care because while it may not cause any difficulties in daily life, it carries a higher risk of developing dementia.

In relation to increasing prevalence, attention should be paid to the cost of dementia care per patient and government budgets for dementia care. According to the "Korean Dementia Observatory 2018" of the Central Dementia Center, the cost of dementia care per patient is 20.74 million won, and the government budget allocated to dementia care is 14.6 trillion won, which accounts for 10% of the country's gross domestic product (GDP ) of 0.8%. According to estimates, the social cost of dementia in South Korea will increase sharply from a total investment of 17.9 trillion won in 2020 to 87.2 trillion won in 2050.

Increases in both dementia prevalence and government budgets for dementia care are global issues encountered in many countries, although specifics may vary by region and population aging development.

In the case of patients with vascular dementia, if the cause of the dementia is stroke, brain tumor, or normal pressure hydrocephalus (NPH), it may be cured by performing surgery. In the case of vascular dementia caused by brain infarction, patients may prevent or delay its development by eliminating or managing high blood pressure, diabetes, smoking, hyperlipidemia and other factors. However, Alzheimer's disease is a degenerative dementia, which is different from patients with vascular dementia. It is difficult to expect the above-mentioned methods to have a positive therapeutic effect on patients with Alzheimer's disease.

Currently, the U.S. Food and Drug Administration approves two types of drugs for the treatment of Alzheimer's disease: cholinesterase inhibitors, such as donepazil, rebastigamine, and galantamine, and N-methyl - D-aspartate antagonists, such as memantine. Donepazil, a cholinesterase inhibitor, is generally prescribed to treat all stages of Alzheimer's disease, while Ribadizamine and Galantamine are used to treat mild to moderate stages of Alzheimer's disease mutism. Memantine is prescribed along with donepazil to treat moderate to severe stages of Alzheimer's disease. However, the therapeutic effect of these drugs is very limited. The drugs mentioned above can only relieve the symptoms, not stop the progression of the disease or cure the disease itself. Meanwhile, since drug therapy bears serious and often fatal side effects, the problem of drug therapy being ineffective for dementia has been raised, and the fact that too many interactions between drugs may be dangerous has been pointed out. In fact, in France, from August 2018, insurance plans have suspended coverage for the four types of dementia treatments mentioned above.

In addition, there are various cases where multinational pharmaceutical companies failed to develop or stopped developing drugs for Alzheimer's disease (eg, Pfizer's Bapineuzumab, Eli Lilly's Solanezumab, Merck's Verubecestat (which is a β-secretase (β-secretase) secretase, BACE) inhibitors), Bellinger Ingelheim's "BI 409306", AstraZeneca's Saracatinib, Biogen's Aducanumab, Novartis and Amgen's "CNP520 (Umibecestat)", Roche's Crenezumab) simply proved Difficulties in developing drugs for Alzheimer's disease. Therefore, no innovative Alzheimer's treatments are expected in the near future.

In this disclosure, based on the Mechanism of Action (MOA) of Amnestic Mild Cognitive Impairment and Alzheimer's Disease, Therapeutic Hypotheses and Digital Therapeutic Hypotheses for the Treatment and/or Developmental Inhibition of Mild Cognitive Impairment and Alzheimer's Disease , provides digital devices and applications for the developmental inhibition and treatment of amnestic mild cognitive impairment and Alzheimer's disease.

The embodiments disclosed herein can be based on the rational design of applications to clinically verify the digital treatment hypothesis and implement the digital treatment for amnestic mild cognitive impairment and Alzheimer's disease.

Mechanisms of action, therapeutic hypotheses, and digital therapeutic hypotheses can be deduced based on the neurofluidic factors of amnestic mild cognitive impairment and Alzheimer's disease. Based on the hypothesis of digital therapy for amnestic mild cognitive impairment and Alzheimer's disease, it is possible to provide reliable digital devices and applications that suppress the progression of amnestic mild cognitive impairment and Alzheimer's disease by repeating digital instructions for patients To develop and deliver improved therapeutic outcomes.

The digital device for mild cognitive impairment and Alzheimer's disease treatment according to an embodiment may include a processor for generating digital indications. For example, the processor generates a digital therapy module for mild cognitive impairment and Alzheimer's disease treatment based on the mechanism of action and treatment hypothesis of mild cognitive impairment and Alzheimer's disease. The processor can further generate specific digital instructions based on the digital therapy module, and provide the above-mentioned instructions to a first user, and can use the device to collect the execution results of the first user on the digital instructions.

A digital application program for mild cognitive impairment and Alzheimer's disease treatment according to an embodiment, as a digital application program stored in a computer-readable medium, can instruct a computing device to perform a plurality of operations, including : Based on the mechanism of action and treatment hypothesis of mild cognitive impairment and Alzheimer's disease to produce a digital treatment module for the treatment of mild cognitive impairment and Alzheimer's disease; based on the digital treatment module to produce a plurality of specific digital instructions; providing the digital instructions to a first user; and collecting a plurality of execution results of the first user for the digital instructions.

As described above, mechanisms of action, therapeutic hypotheses, and digital therapeutic hypotheses can be deduced based on neurofluidic factors in the development of amnestic mild cognitive impairment and Alzheimer's disease. Based on these findings, patients can be given digital tasks, and their execution and completion of the tasks can be collected and analyzed to effectively inhibit the development of amnestic mild cognitive impairment and Alzheimer's disease and provide improved treatment outcomes.

The development of a new drug begins with identifying the medical need in the field, proposing a mechanism of action based on expert review and meta-analysis of the corresponding disease, and deriving a therapeutic hypothesis based on expert review and meta-analysis. And, after preparing the drug library expected to have a therapeutic effect based on the therapeutic hypothesis, candidate materials are found through screening, and the corresponding candidate materials are put into optimization and preclinical tests to check their effectiveness and safety from the preclinical stage, thereby Determine the candidate material as the final drug candidate. In order to mass-produce the corresponding candidate drugs, chemistry, manufacturing, and control (CMC) procedures have also been established, and clinical trials are carried out for the corresponding candidate drugs to verify the mechanism of action and therapeutic hypotheses of the candidate drugs, thereby Ensure the clinical effectiveness and safety of drug candidates.

There are many uncertainties in drug targeting and signaling in the upstream of new drug development. In many cases, novelty of the invention may be difficult to assure because drug targets and signaling employ methods that summarize results already reported in the field and interpret those results. On the contrary, despite the continuous development of research methods for the research and development of many new drugs, in addition to some antibody or nucleic acid (DNA, RNA) treatments, there is still a need for the invention of drugs that can modulate drug targets and signal transduction to treat diseases. Creativity of the highest order. As a result, the molecular structure of a drug is the most critical factor in the field of new drugs.

Unlike drugs, digital therapy is basically achieved using software that implements digital therapy. Due to the nature of digital therapeutics, the rational design of digital therapeutics for corresponding diseases, and the realization of digital therapeutics based on this rational design can be regarded as a very creative process when the clinical validation and approval process is regarded as treatment. That is to say, the core of digital therapy relies on the rational design of digital therapy suitable for the treatment method of the corresponding disease, and the development of specific procedures that can clinically verify digital therapy based on the rational design.

Figure 1A illustrates an exemplary mechanism of action (MOA) for Alzheimer's disease (AD), which can be used in conjunction with any of the other embodiments described herein. Figure 1B illustrates an exemplary treatment procedure based on the therapeutic hypothesis of treating mild cognitive impairment and Alzheimer's disease or inhibiting the development of mild cognitive impairment and Alzheimer's disease, which can be combined with any of the other embodiments described herein use. FIG. 1C illustrates another exemplary treatment program based on a user device for treating or inhibiting the progression of mild cognitive impairment and Alzheimer's disease, which may be compared to the one described herein. Any other embodiment can be used in combination.

Digital devices for inhibiting the progression of mild cognitive impairment and Alzheimer's disease and treating mild cognitive impairment and Alzheimer's disease or can be based on amnestic mild cognitive impairment and Alzheimer's disease through literature searches and expert reviews The mechanism of action and treatment hypotheses derived from the clinical trial articles of the disease are realized.

Generally speaking, disease treatment is by analyzing a certain disease in terms of pathophysiological function and disposition to determine the start point, progression point, and end point of the disease. ongoing. And, the indication of the disease is defined by the characterization of the corresponding disease and the statistical analysis of the disease. Also, analyze the physiological factors of the patient corresponding to the verified indication, especially the neurofluid factors, and limit the patient's neurofluid factors to a narrow range related to the disease to deduce the mechanism of action.

Next, therapeutic hypotheses are derived in which the corresponding disease is treated by manipulating actions and circumstances directly related to the modulation of the corresponding neurofluid factor associated with the disease. In order to implement this therapeutic hypothesis into digital therapy, a digital therapeutic hypothesis is proposed for achieving therapeutic effects by repeating digital instructions and executions related to "controlling actions/environmental adjustments of patients' neurofluidic factors". The digital therapy hypothesis can be implemented as digital devices and applications configured to present changes in patient actions (including behavioral, emotional, and cognitive domains), improvements in the patient's environment, and patient engagement in the form of specific instructions, and collect and analyze the execution of those specific instructions.

Literature searches for clinical trials as described above can be performed through meta-analysis and data mining, and clinical expert feedback and in-depth reviews can be applied at each analysis step. Basically, the embodiments described here include using the above-mentioned procedures to extract the mechanism of action and treatment hypotheses of mild cognitive impairment and Alzheimer's disease, and based on these results to adjust neurofluidic factors to provide digital devices and applications as Digital therapy for inhibiting the development of mild cognitive impairment and Alzheimer's disease and treating mild cognitive impairment and Alzheimer's disease.

However, the method of extracting the mechanism of action and hypothesis of treatment of mild cognitive impairment and Alzheimer's disease is not limited to the above-mentioned methods, and various methods can be used to extract the mechanism of action and hypothesis of treatment of diseases.

Please refer to Figure 1A, various risk factors 105 in the aging process, such as age, genetic/family medical history, smoking and alcohol consumption, arteriosclerosis, cholesterol, serum homocysteine, diabetes, mild cognitive impairment, and other factors, May lead to an imbalance of neurofluid factors during aging. For example, neurofluid factor 110 can include sex steroid hormone abnormalities, insulin-like growth factor-2 (IGF-2) degradation, Wnt/β-catenin abnormalities, BAG1 degradation, cyclic adenosine monophosphate response binding protein (CREB) Neurofluid factor 110 physiologically inhibits neurogenesis in the hippocampus in decline, corticosteroids such as hypersecretion of inflammatory factors, cortisol, and glucocorticoids, and hyposecretion of neurohormones such as dopamine, norepinephrine, and somatostatin , can cause inflammation of brain tissue, and can also lead to stress and depression. Over a long period of time, these physiological abnormalities115 or physiological factors may induce plaque deposition and neuronal apoptosis, resulting in brain atrophy120 with plaque deposition, which is an anatomical feature of Alzheimer's disease . As a result, a clinical syndrome or disease commonly referred to as dementia develops125, which results in malfunctioning of the brain, a decline in cognitive functions such as memory, language, and judgment, thus causing difficulty in performing daily activities.

Please refer to Fig. 1B, mild cognitive impairment and Alzheimer's disease treatment hypotheses are about restoring neurofluidic factors 140 by patient's participation 135 after diagnosis 130 of mild cognitive impairment and/or Alzheimer's disease balance to inhibit the development and treatment of mild cognitive impairment and Alzheimer's disease, patient participation135 includes the patient's behavioral control (eg, lifestyle, habits, exercise, and nutrition ) and environmental controls (eg, bright, familiar, relaxed executive atmosphere settings). Restoring the balance of neurofluidic factors 140 may lead to mild cognitive impairment and/or Alzheimer's disease therapeutic effects 145 .

Please refer to FIG. 1C, the hypothesis of digital treatment of mild cognitive impairment and Alzheimer's disease can be realized by a device 100, which is configured to present changes in patient behavior, improvement of patient environment, and patient participation, and to collect and analyze the implementation of those specific instructions. When digital therapy is used, neurofluid factor imbalances in patients with amnestic mild cognitive impairment and Alzheimer's disease may be corrected through digital input (direction) and output (execution) to achieve mild cognitive impairment and Alzheimer's disease. Developmental inhibition and treatment of mutism.

The mechanisms of action and treatment hypotheses for mild cognitive impairment and Alzheimer's disease described with reference to Figures 1A and 1B are not limited thereto. The method can be applied to other types of mild cognitive impairment and Alzheimer's disease.

Also, while sex steroid hormones, IGF-2, Wnt/β-catenin, BAG1, CREB, inflammatory factors, corticosteroids, and neurohormones are described as neurofluidic factors as shown in Figures 1A and 1B, they should It is understood that the description of neurofluid factors is given by way of illustration only and is not intended to limit all aspects of the mechanisms of action and therapeutic hypotheses for amnestic mild cognitive impairment and Alzheimer's disease.

FIG. 2 is a system diagram illustrating an exemplary device 200 that can be used to inhibit the development of amnestic mild cognitive impairment and Alzheimer's disease and treat amnestic mild cognitive impairment and Alzheimer's disease, which can be compared with the present invention. Any other embodiments described are used in combination. As shown in FIG. 2, the device 200 may include, inter alia, a processor 218, a transceiver 220, a transmit/receive element 222, a speaker/microphone 224, a keypad 226, a display/touch panel 228, a Non-removable memory 230 , a removable memory 232 , a power supply 234 , a global positioning system (GPS) chipset 236 , and/or other peripheral devices 238 . It will be appreciated that apparatus 200 may comprise any subcombination of the foregoing elements while remaining consistent with the embodiments. For example, device 200 may include a mobile device, user equipment (UE), mobile radio, fixed or mobile subscriber unit, subscription-based unit, pager, mobile phone, personal digital assistant (personal digital assistant) digital assistant, PDA), smartphone, notebook computer, light-weight notebook, personal computer, wireless sensor, hotspot or Mi-Fi device, Internet of Things (IoT) device, watch or other wearable mobile devices, head-mounted displays (HMD), vehicles, drones, medical devices and applications (e.g. remote surgery), industrial devices and applications (e.g. in industrial and/or automated process chains) Robots and/or other wireless devices operating in a network), consumer electronic devices, and devices operating on commercial and/or industrial wireless networks, among others.

Processor 218 may be a general purpose processor, a special purpose processor, a conventional processor, a digital signal processor (DSP), a plurality of microprocessors, one or more microprocessors associated with a DSP core, Controllers, microcontrollers, Application Specific Integrated Circuits (ASICs), Field Programmable Gate Arrays (Field Programmable Gate Arrays (FPGAs), any other type of integrated circuit (IC) , and state machines, etc. Processor 218 may perform data processing, power control, input/output processing, sensor data processing, and/or any other functions that enable device 200 to treat mild cognitive impairment and dementia. Processor 218 may be coupled to transceiver 220 , which may be coupled to transmit/receive element 222 . Although FIG. 2 depicts the processor 218 and the transceiver 220 as separate elements, it will be understood that the processor 218 and the transceiver 220 may be integrated together in an electronic package or die.

The transmit/receive element 222 may be configured to transmit data to or receive data from a server located at the medical institution. For example, a medical instruction from a doctor/medical information sensed from a user can be received/transmitted from/to the server via the base station through the wireless interface 216 . In one embodiment, the transmit/receive element 222 may be an antenna configured to transmit and/or receive radio frequency signals. In one embodiment, the transmitting/receiving element 222 may be a transmitter/detector configured to transmit and/or receive signals such as infrared light, ultraviolet light, or visible light. In yet another embodiment, the transmit/receive element 222 may be configured to transmit and/or receive both radio frequency signals and light signals. It will be appreciated that the transmit/receive element 222 may be configured to transmit and/or receive any combination of wireless signals. The transceiver 220 may be configured to modulate signals to be transmitted by the transmit/receive element 222 and to demodulate signals received by the transmit/receive element 222 .

The processor 218 of the device 200 may be coupled to a speaker/microphone 224, a keypad 226, a display/touchpad 228 (e.g., a liquid crystal display (LCD) display unit or an organic light-emitting diode (organic light-emitting diode) diode, OLED) display unit), and/or peripheral devices 238 (eg, sensors or digital cameras), and can receive user input data therefrom. Processor 218 may also output user data or digital indications to speaker/microphone 224 , keypad 226 , display/touchpad 228 , and/or peripherals 238 . Additionally, processor 218 may access information from, and store data in, any type of suitable memory, such as non-removable memory 230 and/or removable memory 232 . Non-removable memory 230 may include random access memory (RAM), read only memory (ROM), hard disk, or any other type of storage/device. The removable memory 232 may include a subscriber identity module (subscriber identity module, SIM) card, a memory stick (memory stick), a secure digital (secure digital, SD) memory card, and the like. In other embodiments, the processor 218 may not be physically located on the device 200, such as a server or a memory on a home computer (not shown), and store data therein.

Processor 218 may receive power from power supply 234 and may be configured to distribute and/or control power to other components in device 200 . Power source 234 may be any suitable device for powering device 200 . For example, the power source 234 may comprise one or more dry battery packs (eg, nickel cadmium (NiCd), nickel zinc (NiZn), nickel metal hydride (NiMH), lithium ion (Li-ion), etc.), solar Batteries, and fuel cells, etc.

Processor 218 may also be coupled to GPS chipset 236, which may be configured to provide location information (eg, longitude and latitude) regarding the current location of device 200 . In addition to or instead of information from GPS chipset 236, device 200 may receive location information from a base station over wireless interface 216 and/or determine its location based on the timing of information received from two or more nearby base stations. It will be appreciated that the device 200 may obtain location information by any suitable location determination method while remaining consistent with the embodiments.

The processor 218 may further be coupled to other peripheral devices 238, which may include one or more software and/or hardware modules that provide additional features, functions, and/or wired or wireless connections. Peripherals 238 may include, for example, accelerometers, electronic compasses, satellite transceivers, digital cameras (for photos and/or videos), universal serial bus (USB) ports, vibrating devices, television transceivers , hands-free headsets, Bluetooth® modules, frequency modulated (FM) radios, digital music players, media players, video game player modules, Internet browsers, virtual reality and/or Or Augmented Reality (Virtual Reality and/or Augmented Reality, VR/AR) devices, and activity trackers, etc. Peripherals 238 may include one or more sensors. The sensors can be gyroscopes, accelerometers, hall effect sensors, magnetometers, orientation sensors, proximity sensors, temperature sensors, time sensors, geolocation sensors, altimeters, light One or more of sensors, touch sensors, magnetometers, barometers, gesture sensors, biometric sensors, and humidity sensors, among others.

Processor 218 may perform generation of digital indications, collection of sensory data, input for execution, analysis of results, communication with databases, and security functions.

Based on the mechanism of action, treatment hypothesis, and digital treatment hypothesis of amnestic mild cognitive impairment and Alzheimer's disease, a doctor (for example, a second user) can prescribe digital treatment for the corresponding patient, which is currently used for treatment Mild Cognitive Impairment and Alzheimer's Disease in Digital Devices and/or Apps. In one example, the processor 218 may be configured to provide a digital therapeutic prescription to the patient based on the interaction between the neurofluidic factors of mild cognitive impairment and Alzheimer's disease and the patient's behavior/environment, as a patient-executable Specific behavior instructions. For example, these nerve fluid factors may include, but are not limited to, sex steroid hormones, IGF-2, Wnt/β-catenin, BAG1, CREB, multiple inflammatory factors, multiple corticosteroids, and multiple neurohormones, which can Consider all types of neurofluidic factors that can cause disease.

Processor 218 may generate digital instructions based on input from the physician. In this case, the processor 218 may generate a digital indication based on information collected by the doctor when diagnosing the patient. Also, the processor 218 may generate a digital indication based on information received from the patient. For example, information received from a patient may include the patient's basal factors, medical information, and digital therapy literacy. In this case, essential factors may include the patient's activity, heart rate, sleep, and diet (nutrients and calories), among others. Medical information may include a patient's electronic medical record (EMR), family medical history, genetic vulnerability, and genetic susceptibility, among others. Digital therapeutic literacy can include patient accessibility and acceptance of digital therapeutic instructions and devices, among others.

The processor 218 can reflect the mechanism of action and treatment hypotheses of MCI and Alzheimer's disease to use one or more hypothetical parameters and generate digital models. In this case, hypothetical parameters may be derived for neurogenesis, anti-inflammation, anti-stress, and anti-depression in the hippocampus, taking into account the patient's environment, behavior, emotion, and cognition. The hypothetical parameters are further detailed as shown in Figure 5A.

Processor 218 may generate digital indications specifically designed to allow the patient to have therapeutic effects and provide these indications to the patient. For example, the processor 218 can generate specific digital instructions in each digital therapy module.

The processor 218 may perform data collection and performance input capable of collecting performance results of the patient for the digital indication. Specifically, the processor 218 is configured to sense the patient's adherence to the digital indication, and allow the patient to directly input the execution result of the digital indication, and thus be used to output the patient's execution result of the digital indication.

The processor 218 may collect the patient's behavioral persistence or participation for a predetermined period and report the patient's behavioral persistence or participation to an external system. Therefore, even if the patient does not go directly to the hospital, the doctor can continue to monitor the execution process of the digital instructions through the application.

The database can store the mechanism of action and treatment hypotheses of mild cognitive impairment and Alzheimer's disease, the digital instructions provided to the user, and the user's execution result data. Although not shown in FIG. 2, the database may be included in a device 200 for treating amnestic mild cognitive impairment and Alzheimer's disease. Alternatively or additionally, the database can be provided on an external server.

At the same time, a series of loops including inputting the digital indication, outputting the execution result of the patient on the digital indication, and evaluating the execution result can be repeated several times. In this case, the processor may generate a patient-specific digital indicator for this cycle by reflecting the patient digital indicator and output values and evaluations provided in the previous cycle.

As described above, the device 200 for inhibiting the development of amnestic mild cognitive impairment and Alzheimer's disease and treating amnestic mild cognitive impairment and Alzheimer's disease can Neurofluid Factors in Alzheimer's Disease Deduced mechanisms of action, therapeutic hypotheses, and digital therapeutic hypotheses to inhibit the development of amnestic mild cognitive impairment and Alzheimer's disease and provide improved therapeutic outcomes. Apparatus 200 may provide digital indications based on these findings, and collect and analyze performance results.

FIG. 3 is a diagram illustrating an exemplary input and output cycle of a user device for treating or inhibiting the development of mild cognitive impairment and Alzheimer's disease, which may be used in conjunction with Any other embodiments described herein are used in combination.

Please refer to FIG. 3 , according to an embodiment, the digital application program for treating mild cognitive impairment and Alzheimer's disease can provide corresponding digital prescriptions for patients in the form of instructions. The execution result indicated by the corresponding digit can be recursively input into the application program as an input.

Digital instructions provided to the patient may include specific action instructions and control of the patient's light environment. As shown in FIG. 3, the digital indications may include, but are not limited to, implementation environment settings, life style, learning, exercise, and positive/achievement.

The results of the patient's execution of the digital instructions can include: (1) login/logout information of instructions and execution; (2) passive data such as motion, stress-related heart rate, and oxygen saturation changes and etc.; and (3) direct input information of patient execution results.

Figure 4 is a diagram illustrating an exemplary feedback loop for treating mild cognitive impairment and Alzheimer's disease or inhibiting the development of mild cognitive impairment and Alzheimer's disease, which can be implemented with any other described herein Examples are used in combination.

Please refer to Figure 4, the developmental inhibition and treatment of mild cognitive impairment and Alzheimer's disease can be achieved by repeatedly executing the single feedback loop of Figure 3 mentioned above to regulate neurofluidic factors.

In cases of mild cognitive impairment and Alzheimer's disease, ongoing digital therapy and observation are required. Due to these properties, inhibition of the development of mild cognitive impairment and Alzheimer's disease can also be achieved by gradually improving the instruction-execution cycle in the feedback loop, as opposed to simply repeating the instruction-execution cycle during the corresponding course of therapy and therapeutic effects. For example, the digital indication and execution result about the first cycle are given as the input value and output value of a single cycle, but when the feedback loop is executed N times, it can be reflected in this time by using the feedback program of the cycle The input value and output value generated in the cycle are used to generate a new digital indication to adjust the input about the next cycle. This feedback loop can be repeated to derive patient-specific digital instructions while maximizing therapeutic efficacy.

Therefore, in the digital device and the application program, the digital indication of the patient provided in the previous cycle (for example, the N-1th cycle) and the data indicating the execution result can be used to calculate the current cycle (for example, the N-th cycle). Patient digit indication and execution results in cycle). That is to say, the digital indications in the next cycle can be generated based on the patient digital indications calculated in the previous cycle and the execution results of these digital indications. In this case, various algorithms and statistical models can be used in the feedback procedure if necessary.

As described above, in digital devices and applications for the treatment of mild cognitive impairment and Alzheimer's disease, it is possible to optimize patient-specific digital instructions for patients through rapid feedback loops.

Figure 5A is a diagram illustrating an exemplary module for implementing digital therapy for treating or inhibiting the progression of mild cognitive impairment and Alzheimer's disease, which may be used in conjunction with the Any other embodiments described herein are used in combination. FIG. 5B is a diagram illustrating exemplary contextual factors supporting a user device for treating or inhibiting the development of mild cognitive impairment and Alzheimer's disease, which may be compared with those herein Any other embodiments described are used in combination.

As shown in Figure 5A, when creating therapeutic hypotheses based on the mechanism of action of mild cognitive impairment and Alzheimer's disease, target neurofluid factors 505 (e.g., sex steroid hormones, IGF-2, Wnt/β-catenin protein, BAG1, CREB, inflammatory factors, corticosteroids, and neurohormones, etc.). A plurality of hypothetical parameters 510 may be used to allow specific indications to correspond to the adjustment of these neurofluid factors 505 . A plurality of modules 500 for treating mild cognitive impairment and Alzheimer's disease can be derived using the "nervous fluid factor-hypothetical parameter-module" correlation. Each module 500 may be described in the form of a module designation, see FIGS. 7A-7E for further details. In this case, each module 500 is a basic design unit for digital therapy implemented in an actual digital device or an application program, and is a collection of specific instructions.

Specifically, please refer to Figure 5A, the neurofluid factor 505 deduced based on the mechanism of action and treatment hypothesis of mild cognitive impairment and Alzheimer's disease may include but not limited to sex steroid hormones, IGF-2, Wnt/β -Catenin, BAG1, CREB, inflammatory factors, corticosteroids, and neurohormones. In order to treat mild cognitive impairment and Alzheimer's disease, it can balance sex steroid hormones, increase the secretion of IGF-2, balance Wnt/β-catenin, increase the secretion of BAG1 and CREB, and reduce the secretion of inflammatory factors and corticosteroids. Secrete, and increase the secretion of neurohormones to deal with the imbalance of nerve fluid factors.

In order to further elaborate the relationship of "neural fluid factor-hypothetical parameter-module" from the perspective of molecular biology, neurophysiology and pathology, the specific category of each neurofluid factor can be explained: 1) The neurons in the hippocampus Generative, related to the consolidation of declarative-semantic memory, ii) anti-inflammatory, related to the consolidation of episodic memory, iii) anti-stress and anti-depressant.

Although nearly all mammals, including humans, undergo continuous neurogenesis throughout life, in general, active adult neurogenesis occurs only in limited brain regions where neurogenesis is particularly pronounced (the dentate gyrus of the hippocampus). The subgranular zone (SGZ) and the subventricular zone (SVZ) of the lateral ventricles). Adult neurogenesis in other regions of the central nervous system (CNS) is known to be highly restricted under normal physiological conditions.

With regard to the development of amnestic mild cognitive impairment and Alzheimer's disease, impairment of declarative-semantic memory is first observed. In order to treat or inhibit this development, neurogenesis in the hippocampus has recently received attention, and genes and proteins related to neurogenesis can be used as targets for the development of dementia therapeutic drugs.

Neurogenesis in the hippocampus is associated with sex steroid hormones, IGF-2, Wnt/β-catenin, BAG1, or CREB, among others.

The decline in estrogen after menopause (i.e. sex steroid hormone imbalance) accounts for the relatively high prevalence of dementia in women, which is twice as high as that in men. In a randomized controlled trial (RCT) of the effects of hormone replacement therapy (HRT) on cognitive function in postmenopausal women, only the HRT treatment group showed the Montreal Cognitive Assessment (Montreal Cognitive Assessment, MoCA) scores increased significantly, in other words cognitive performance improved. MoCA is a screening test for mild cognitive impairment and Alzheimer's disease, and has been adopted by many hospitals.

Light is known to help improve cognitive function in humans. However, the neurobiological mechanisms underlying this positive effect of light have not been recognized. Recently, studies of diurnal timing using trained mice reported an association between long-day exposure and increases in IGF-2 (a locally secreted insulin-like growth factor), as well as between long-day exposure and long-term recognition in the hippocampus ( Recognition) the correlation between memory enhancement.

Wnt signaling plays an important role in nervous system development and adult synaptic plasticity. Especially in learning and memory, Wnt signaling may play a key role in the normal function of the hippocampus. Wnt/β-catenin E2/E4 balance is associated with memory solidification-storage-recall in declarative memory areas through learning.

The BAG gene is associated with aging-related neurodegenerative diseases such as Alzheimer's disease and is a determinant of neuronal differentiation. It may play a direct role in CREB (cyclic adenosine monophosphate-responsive binding protein) memory-associated synaptic plasticity. BAG1/CREB is associated with neurogenesis in the hippocampus, which has recently been reported to control neurons in the hippocampus through defense responses elicited by treat- and extinction-signaling brain networks generate.

By using the hypothetical parameters 510 of neurogenesis in the hippocampus to map the above-mentioned neurofluid factors 505 to the action instructions of the digital therapy module 500, it is possible to control/improve the imbalance or insufficiency of the neurofluid factors through action instructions to achieve imbalances. Therapeutic effect of mental illness. Examples specifically linking action instructions and neurofluidic factors associated with neurogenesis in the hippocampus can include improvement of sex steroid hormones through dietary control, increased IGF-2 secretion through a favorable light environment, restoration of Wnt/β- Catenin homeostasis, and BAG1/CREB brain neural network activation by experience in treatment and extinction episodes.

Anti-inflammation is related to inflammatory factors. Inflammatory factors may interfere with the freezing of event memory and aggravate dementia by interrupting the recall of declarative memory. By using the hypothetical parameters of anti-inflammation to map the inflammatory factors to the action instructions of the digital therapy module, the high degree of inflammation can be controlled/improved to achieve the therapeutic effect of dementia.

Stress resistance is associated with corticosteroids, including cortisol and glucocorticoids. Antidepressants are associated with neurohormones, including dopamine, norepinephrine, and somatostatin. Imbalances of corticosteroids and neurohormones negatively affect neurogenesis and disposition in the hippocampus. By using hypothetical parameters of anti-stress and anti-depression to map corticosteroids and neurohormones to the action instructions of the digital therapy module, the imbalance of corticosteroids and neurohormones can be controlled/improved to achieve the therapeutic effect of dementia. Instructions for action related to anti-inflammation, anti-stress, and anti-depression can include a safe and familiar executive environment, a nutritious diet, as well as exercise and normal sleep induction.

In summary, the control of each neurofluid factor 505 can be mapped to the digital therapy module 500 by using hypothetical parameters 510 such as neurogenesis in the hippocampus, anti-inflammation, anti-stress, and anti-depression. Also, specific digital indications for each module can be constructed based on the digital therapy modules. Meanwhile, the digital indications can include execution environment settings and modules such as life style, study, exercise, affirmation/achievement, or similar modules. However, the modules of this embodiment are not limited thereto.

The control of each neurofluid factor 505 corresponds to the digital therapy module 500 using hypothetical parameters 510 such as neurogenesis in the hippocampus, anti-inflammation, anti-stress, and anti-depression. Then, a specific digital indication for each module can be generated based on the converted modules. In this case, digital indications may include implementation environment settings and modules (eg life style, learning, exercise, affirmation/achievement), which can be output by monitoring. However, these modules 500 are given by way of illustration only and are not intended to be limiting of the modules 500 .

Please refer to FIG. 5B , in the design of the digital device and application program modules for treating mild cognitive impairment and Alzheimer's disease according to an embodiment of the present invention, background factors can be considered comprehensively.

In this case, the background factor is an element necessary to correct the clinical trial results during the verification of the clinical effectiveness of the digital therapy for mild cognitive impairment and Alzheimer's disease. Specifically, among the background factors shown in FIG. 5B , the basic factors 550 may include but not limited to activity, heart rate, sleep, and diet (nutrition and calories) and the like. Medical information 555 may include, but is not limited to, electronic medical records, family medical history, genetic vulnerabilities, and predispositions, among others. The medical information can be filled in when the patient visits the hospital. Digital therapeutic literacy or understanding 560 may include, but is not limited to, patient accessibility and acceptance of digital therapeutic instructions and devices.

Figure 6A is a diagram illustrating an exemplary method of specifying a patient-specific prescription, which may be used in conjunction with any of the other embodiments described herein. FIG. 6B illustrates an exemplary method of specifying a patient-specific digital prescription based on the analysis of a plurality of digital indications and the execution of the digital indications, which may be used in conjunction with any of the other embodiments described herein.

In this way, when using digital devices and applications (APPs) for the treatment of mild cognitive impairment and Alzheimer's disease, medical professionals such as doctors can check the patient's indications and The results were executed and adjusted in a patient-specific manner for the types of modules used to treat mild cognitive impairment and Alzheimer's disease and the indications for each module, as shown in Figure 6B.

FIG. 7A is a diagram illustrating an exemplary digital indication of an execution environment setting, which may be used in conjunction with any of the other embodiments described herein. Fig. 7B is a diagram illustrating an exemplary digital indication of a lifestyle module, which may be used in conjunction with any of the other embodiments described herein. Fig. 7C is a diagram illustrating an exemplary digital indication of a memory/learning module, which may be used in conjunction with any of the other embodiments described herein. FIG. 7D is a diagram illustrating an exemplary digital indication of a motion module, which may be used in conjunction with any of the other embodiments described herein. FIG. 7E is a diagram illustrating an exemplary digital indicator of a positive/achievement module, which may be used in conjunction with any of the other embodiments described herein.

For digital therapy for mild cognitive impairment and Alzheimer's disease, it is important that participants are interested in digital therapy and voluntarily participate in therapy as an ongoing treatment. In this article, mods can be configured by adding game elements to each mod. In digital devices and applications for inhibiting the development of mild cognitive impairment and Alzheimer's disease and treating mild cognitive impairment and Alzheimer's disease, as will be described below, each module includes specific instructions gather.

Please refer to FIG. 7A, which shows a specific example of executing the instruction of environment setting and the method of collecting output data. In this case, the execution environment settings can be included as part of the configuration generated by the digits described above. Other modules shown in Figures 7B to 7E can be executed under the bright, familiar, relaxed environment of the execution environment setting of Figure 7A.

Brightness settings can include but are not limited to using illuminance sensors or smart lamps (IoT lamps) to set digitally indicating the brightness of the execution environment, creating a living environment where a person can be exposed to bright environments such as at least 16 hours a day.

Comfort or familiarity settings can include application context settings (e.g., content that may help the patient recall past memories, such as the patient's favorite song, scenes and lines from the patient's favorite movie, family photos, documentary photography, etc.) and A location setting configured to help the patient recall memories in a familiar and friendly environment during the performance of instructions.

Behavior or relaxation settings can include application environment settings (e.g., content that may help relieve stress, such as background wallpapers, music, tones, etc.), which provide a relaxing atmosphere to perform instructions, and location settings, which can be used during instructions. Provides tranquility during execution.

Figures 7B-7E illustrate examples of specific instructions for each module, and methods for collecting output data. In these embodiments, the modules can include lifestyle, learning, exercise, affirmation (or positive)/achievement modules.

Please refer to FIG. 7B, which shows a specific example of the instructions of the life style module and the method of collecting output data. In this case, the Lifestyle module can be included as part of the above-described digital indication generation configuration.

Instructions for new experiences and travel can include weekly or fortnightly trips to new places to experience new surroundings. New experiences and trips (instructions) can involve recording (executing) using journals or various digital media.

Sex Hormone Balance Indication is designed to recover from a fundamental imbalance in sex steroid hormones caused by aging or menopause. In particular, menopausal women who have undergone radical changes in sex hormones are advised to avoid HRT (hormone replacement therapy) or strict diets that lead to radical fat loss. Retrieved hormone balance indications through meals reflecting nutritional balance may include, but are not limited to, dietary records and nutritional assessments (perform).

Please refer to FIG. 7C , which shows a specific example of the instructions of the learning module and the method of collecting output data. In this case, the learning module can be included as part of the configuration for digital indication generation described above.

Specifically, the instructions of the learning module can include behavioral instructions for patients to continuously repeat and recall familiar things in a relaxed atmosphere. In the case of a learning mod, the first user's execution can be performed in the form of a game record of the logbook, which facilitates memorization and learning. Also, a comfortable environment for connected learning can be provided with digital therapy backgrounds, tones, and music settings. For example, the instructions of the learning module can induce the user to listen to soothing music or smell good smells.

Please refer to FIG. 7D, which shows a specific example of the instruction of the motion module and the method of collecting output data. In this case, the body movement module can be included as part of the configuration for digital indication generation described above.

An exercise module may include a series of behavioral instructions that, for example, define 20 minutes of vigorous exercise on a regular basis (eg, 3 times a week).

Specifically, the behavior indication of the exercise module may include the use of neurobiological feedback devices (for example, electroencephalogram (EEG), electrocardiogram (ECG), electromyography (EMG), electrodermal graph (EDG), etc.) or A method of collecting performance results by collecting sensing data from general sensors (eg, activity, heart rate, etc.), or a method of allowing patients to directly input the performance results using the performance input as described above. In this case, exercise instruction may be organized according to the patient's age and physical condition using exercise therapy widely used by doctors or motor therapists.

In the case of the exercise module, the first user is able to perform behavioral instructions by writing an exercise log, checking heart rate, or getting a personal training (Pt) trainer.

Please refer to FIG. 7E, which shows a specific example of the indication of the affirmative (or positive)/achievement module, and the method of collecting output data. In this case, the affirmation (or positive)/achievement module can be included as part of the above-described digital indication generation configuration.

Specifically, the affirmation (or positive)/achievement module can contain instructions to stimulate dopamine secretion by the patient performing the task and the gratification of completion. In this case, the task completion indication may be an indication that the patient feels a sense of accomplishment by completing a given task, wherein the patient can renew the task according to the deadline and can induce their voluntary participation. For example, the specific format of the game can vary according to learning, spot the difference or find the difference games, quizzes, and the like.

In particular, it is further expected that the implementation of quiz-style sections from the achievement module will enhance patients' health information literacy and digital therapy literacy. This type of capacity building may be necessary for patients to continue to participate in treatment and improve the patient's performance status.

In the case of the affirmative (or positive)/achievement module, the first user can perform the task in a plurality of ways such as self-feedback, self-reward, reward from the doctor based on the doctor-patient relationship, and the like.

As mentioned above, digital therapy may require long-term ongoing patient participation. Diligent participation during therapy can generate praise (reward) tasks in the affirmation (or positive)/achievement module, allowing patients to feel a sense of accomplishment. In the praise task, patients who actively participate in treatment can be compensated by rewards and trust in the relationship between the patient and the guardian and/or the relationship between the patient and the doctor.

At the same time, mild cognitive impairment is closely related to the development and aging of Alzheimer's disease. In particular, during the aging period, age, gender, personality, and preferences, there are large gaps in the standards for new life styles, learning, sports, affirmation (or positive)/achievement setting. In order to bridge the gap, it is desirable to propose for each module an exclusive digital indication related to the individual characteristics of each patient. In particular, instructions that need to be communicated with applications can be developed by combining big data analysis and artificial intelligence analysis.

The digital indications illustrated in FIGS. 7B to 7E are given by way of illustration only and are not intended to limit the present invention. For example, the digital indication provided to the patient can be set in various ways as necessary.

Figure 8 is a diagram illustrating an exemplary procedure for using a digital application for treating or inhibiting the progression of mild cognitive impairment and Alzheimer's disease, which can be compared to that described herein Any other embodiment of the combination used.

Please refer to FIG. 8, in step 810, according to an embodiment of the digital application program for treating mild cognitive impairment and Alzheimer's disease, it can firstly be based on the mechanism of action of mild cognitive impairment and Alzheimer's disease and therapeutic hypotheses to generate a digital therapeutic module for the treatment of mild cognitive impairment and Alzheimer's disease. In this case, based on neurofluidic factors (eg, sex steroid hormones, IGF-2, Wnt/β-catenin, BAG1, CREB, inflammatory factors, corticosteroids) associated with mild cognitive impairment and Alzheimer's disease , and neurohormones, etc.) to generate digital therapy mods.

Alternatively or additionally, at step 810, a digital therapy module may be generated based on input from a medical professional (eg, a doctor). In this case, the digital therapy module can be generated based on the information collected by the medical professional when diagnosing the patient and the prescription results recorded based on this information. Also, at step 810, a digital therapy module may be generated based on information received from the patient (eg, fundamental factors, medical information, digital therapy literacy, etc.).

In step 820, a plurality of specific digital indications can be generated based on the digital therapy module. For example, mild cognitive impairment and Alzheimer's can be achieved by taking multiple hypothetical parameters about the patient's environment and behavior (eg, neurogenesis in the hippocampus, anti-inflammation, anti-stress, and anti-depression) Mechanisms of action and therapeutic hypotheses for Alzheimer's disease to generate a digital therapy module. This digital therapy module has been described with reference to Fig. 5A and Fig. 5B, so its description will be omitted.

In this case, a digital indication may be generated for performing at least one of environmental settings, life style, learning, exercise, and positive/achievement. The description of the execution environment setting and the specific digital indication of each module is as described in Fig. 7A to Fig. 7E.

At step 830, the digital indications may be provided to the patient. In this case, the digital indication may be provided in the form of a digital indication that is related to behavior, emotion, and cognition and where sensors can be used to monitor the patient's indicated adherence, such as lifestyle and body movement, or where the patient is allowed to Provided in the form of a digital indication of the direct input execution result.

After the patient performs the presented digital instructions, at step 840, a plurality of execution results of the patient for the digital instructions may be collected. For example, the execution result of the digital indication can be collected by monitoring the patient's adherence to the digital indication or allowing the patient to input the execution result of the digital indication as described above.

Meanwhile, the digital application program for treating mild cognitive impairment and Alzheimer's disease according to an embodiment can repeatedly perform a plurality of operations several times, wherein the operations include generating digital indications and collecting the patient's response to the digital indications. execution result. In this case, generating the digital indication may include generating the patient digital indication for the current cycle based on the patient digital indication provided in the previous cycle and the collected execution result data for the patient digital indication.

As described above, the mechanism of action, therapeutic hypotheses, and digital therapeutic hypotheses can be deduced in consideration of neurofluid factors in the development of amnestic mild cognitive impairment and Alzheimer's disease. Based on these findings, patients will be given digital tasks, and their execution and completion of the tasks will be collected and analyzed to effectively inhibit the development of amnestic mild cognitive impairment and Alzheimer's disease and provide improved treatment outcomes.

Although the digital devices and applications for treating mild cognitive impairment and Alzheimer's disease have been described in relation to mild cognitive impairment and Alzheimer's disease treatment, the present invention is not limited thereto. For diseases other than mild cognitive impairment and Alzheimer's disease, digital therapy can be performed in substantially the same manner as described above.

Figure 9 is a diagram illustrating an exemplary procedure for generating digital indications to treat or inhibit the development of mild cognitive impairment and Alzheimer's disease, which may be compared with those described herein Any other embodiment can be used in combination.

Figure 9 further describes the mechanism of action and treatment assumptions for mild cognitive impairment and Alzheimer's disease as described in Figure 5A, Figure 5B, and Figure 8 to produce a method for treating mild cognitive impairment and Alzheimer's disease Alzheimer's disease modules and specific digital instruction programs.

At step 910, mechanisms of action and treatment hypotheses for mild cognitive impairment and Alzheimer's disease can be entered. In this context, as described above, the mechanisms of action and therapeutic hypotheses for MCI and Alzheimer's disease can be predicted by literature searches and expert reviews of systematically relevant clinical trials in MCI and Alzheimer's disease. derived.

In step 920, neurofluidic factors related to mild cognitive impairment and Alzheimer's disease can be predicted from the input mechanism of action and treatment hypotheses. In this case, the neurofluid factors predicted in step S920 can be derived in the form of sex steroid hormones, IGF-2, Wnt/β-catenin, BAG1, CREB, inflammatory factors, corticosteroids, or neurohormones, etc. . These neurofluid factors have already been described in detail with reference to Fig. 5A, and thus description thereof will be omitted.

At step 930, a digital therapy module may be generated based on predicted neurofluid factors corresponding to hypothetical parameters. Here, hypothetical parameters can be used as converters, which convert neurofluid factors related to mild cognitive impairment and Alzheimer's disease into digital therapy modules, and this process is to set the interaction between neurofluid factors and environmental and behavioral factors. Physiological relationship, as shown in Figure 5A.

In step 940, a plurality of specific digital indications may be generated based on the generated digital therapy module. In this case, the specific digital indication can be achieved by referring to the execution environment setting described in Fig. module to generate.

Figure 10 is a diagram illustrating an exemplary procedure for repeatedly performing digital instructions based on feedback regarding treating or inhibiting the development of mild cognitive impairment and Alzheimer's disease, which may be used in conjunction with Any other embodiments described herein are used in combination.

In FIG. 10 , it is explained that digital instruction generation and execution result collection in the digital application for treating mild cognitive impairment and Alzheimer's disease is performed a plurality of times (for example, N times). In this case, at step 1010, the mechanism of action and treatment hypotheses of mild cognitive impairment and Alzheimer's disease may be input first. And, in step 1020, the digital indication and execution result information provided in the previous cycle may be received. When the first cycle of execution is currently being performed, step 1020 can be omitted because there is no previous data.

At step 1030, a digital indication for this cycle may be generated based on the input mechanism of action and treatment hypothesis, the digital indication provided in the previous cycle, and the execution result data. In step 1040, the execution result of the user on the generated digital instruction can be collected.

In step 1050, it is determined whether the current cycle is greater than the Nth cycle. If this cycle is less than the Nth cycle (ie, NO), this can go back to step 1020 again, so steps 1020 to 1040 are repeated. On the other hand, if the current cycle is greater than the Nth cycle (ie, yes), that is, when the generation of the digital indication and the collection of the execution result are performed N times, the feedback operation may be terminated. The number N may be preconfigured, predetermined, or determined by a medical professional according to the state of the patient.

Figure 11 is a diagram illustrating another exemplary procedure for repeatedly performing digital instructions based on feedback regarding treating or inhibiting the development of mild cognitive impairment and Alzheimer's disease, which may Used in conjunction with any of the other embodiments described herein.

Please refer to FIG. 11, which illustrates that digital instruction generation and execution result collection in the digital application for treating mild cognitive impairment and Alzheimer's disease is repeatedly performed. For example, at step 1110, if the mechanism of action and treatment hypotheses for mild cognitive impairment and Alzheimer's disease were input at step 1100, a digital indication may be generated. If a first cycle of execution is in progress, at step 1100 the first treatment hypothesis is entered as 0 (eg, TH 0). Moreover, in step 1120, the execution result data of the digital action instruction of this cycle can be collected.

At step 1130, it may be determined whether the current cycle has sufficient therapeutic effect. If deemed adequate, the same treatment hypothesis is entered at step 1140 for the next cycle. If not, at step 1150 a new treatment hypothesis can be generated based on the action instructions and execution results of this cycle.

The algorithm above illustrates the feed-per-cycle procedure for mild cognitive impairment and Alzheimer's disease-based treatment hypotheses to obtain action instructions and execution results from the patient, which helps to derive the best results for each patient. treatment effect.

The determination at step 1130 may be made by a physician monitoring the digital indication and the results of the execution. However, not all instruction-execution cycles need to be determined. Doctors can make judgments by periodically collecting and analyzing the execution results of different action instructions, such as a period prescribed by the doctor, a period of days, a period of weeks, and a period of months.

Steps 1150 to 1110 illustrate the process of creating new treatment hypotheses to generate the best course of action for patient treatment. As described in FIGS. 5A and 5B , using the "neurofluid factor-hypothetical parameter-module" correlation, at step 1150 new weights for the neurofluid factor can be generated based on the new treatment hypothesis. Changes in weights may be converted into weights for each of the digital therapy modules at step 1110 . For example, through the feedback loop from step 1150 to step 1110, the combination of each module, the number of repetitions of each module, execution time, and intensity, etc. can be optimized.

Figure 12 is a diagram illustrating an exemplary procedure for treating a patient with mild cognitive impairment or dementia by digital therapy, which may be used in conjunction with any of the other embodiments described herein. As illustrated in FIG. 12, at step 1210, a medical professional (e.g., a physician) may determine whether a patient has mild cognitive impairment or dementia based on one or more symptoms of mild cognitive impairment or dementia . If the patient is diagnosed with mild cognitive impairment or dementia at step 1220, a medical professional may prescribe or administer one or more digital therapies to the patient to improve the patient's condition causing the patient's mild cognitive impairment or dementia. A plurality of neurofluid factors. These neurofluid factors may include, but are not limited to, sex steroid hormones, insulin-like growth factor-2 (IGF-2), β-catenin in Wnt signal transduction, Bcl-2-related anti-apoptotic gene 1 (BAG1), Cyclic AMP-responsive binding protein (CREB), multiple inflammatory factors, multiple corticosteroids, or multiple neurohormones. More specifically, the corticosteroids may include Cortisol and glucocorticoids, and the neurohormones may include dopamine, norepinephrine, and somatostatin.

Digital therapy prescribed or administered by a medical professional may include one or more digital instructions produced to treat neurofluid factors based on changes in the neurofluid factors out of balance. Neurofluid imbalances (i.e., imbalances in neurofluidic factors) that may have contributed to the patient's mild cognitive impairment or dementia may include, but are not limited to, sex steroid hormone imbalances, IGF-2 reduction, beta-catenin degradation, BAG1 inactivation , CREB inactivation, increased inflammatory factors, increased corticosteroids, or decreased neurohormones.

Patients can implement the one or more digital instructions to improve their neurofluid imbalance. Examples of digital indications may include, but are not limited to, setting an execution environment, changing a lifestyle, learning, moving, affirming, or accomplishing a task. Neurofluidic changes resulting from the patient's execution of digital instructions may include, but are not limited to, neurogenesis, anti-inflammation, anti-stress, or anti-depression in the patient's hippocampus. In particular, in digital instructions, at least one of setting the execution environment, changing the lifestyle, or learning can be associated with neurogenesis in the patient's hippocampus to treat sex steroid hormone imbalance, IGF-2 reduction, beta-catenin At least one of protein degradation, BAG1 inactivation, and CREB inactivation. In the digital instructions, at least one of setting the execution environment and learning can be associated with anti-stress to treat corticosteroid increases. In digital indications, exercise can be associated with anti-inflammation to treat increased inflammatory factors. In the numerical indications, at least one of performing context, affirmation, and achievement tasks is set to be associated with antidepressant to treat neurohormonal decline.

At step 1240, the medical professional may receive or monitor results of the patient's performance with respect to the one or more digital indicators. The patient's performance of the one or more digital indications may be repeated a predetermined number of times to improve the neural fluid imbalance. After receiving or monitoring the patient's performance, at step 1250, a different or the same digital indication may be generated by the device or under the supervision of a medical professional. The resulting digital indications based on the results of the patient's performance can be used to treat these neurofluid factor imbalances.

In one embodiment, the patient can directly use the user device or device to treat the patient's mild cognitive impairment or dementia. For example, the device may produce one or more digital therapeutics to improve neurofluidic factors in patients with mild cognitive impairment or dementia. The digital therapy may include one or more digital instructions generated to induce at least one of the neurofluid factors based on the patient's performance of the one or more digital instructions Changes to treat an imbalance of at least one of the neurofluidic factors. The device may also be configured to generate a different or the same digital indication based on the patient's performance with respect to the one or more digital indications to treat at least one imbalance of the neurofluid factor in the patient.

The device may communicate with a database of other devices (eg, a server) to report results of the patient's performance with respect to the one or more digital indicators. For example, a device used by a patient may transmit the results of the patient's performance to the digital indication to a server for a medical facility (eg, a hospital) or a device used by a medical professional. The device used by the patient may also receive the second digital indication from another device, such as a server. The second digital indication may be the same as or different from the digital indication performed and reported by the patient. The second digit indication may be indicated by a device used by a medical professional or a medical institution.

FIG. 13 is a diagram illustrating an exemplary hardware configuration of a user device for treating or inhibiting the progression of mild cognitive impairment and Alzheimer's disease, which may be used in conjunction with the Any other embodiments described are used in combination.

Please refer to FIG. 13, the hardware of the digital device for treating mild cognitive impairment and Alzheimer's disease may include a central processing unit 1310, a memory 1320, an input/output interface 1330, and a communication interface 1340 .

The central processing unit 1310 may be a processor configured to execute digital programs for treating mild cognitive impairment and Alzheimer's disease stored in the memory 1320, and various programs for digitally treating mild cognitive impairment and Alzheimer's disease may be processed. Alzheimer's disease data and perform functions related to mild cognitive impairment and Alzheimer's disease digital therapy. That is to say, the central processing unit 1310 can start to execute each configured function by executing the digital programs stored in the memory 1320 for treating mild cognitive impairment and Alzheimer's disease.

The memory 1320 can have stored therein digital programs for treating mild cognitive impairment and Alzheimer's disease. Moreover, the memory 1320 may contain the data contained in the database used in the digital treatment of mild cognitive impairment and Alzheimer's disease, for example, the digital indication of the patient, the execution result of the indication and the medical information of the patient, etc.

The memory 1320 can be a volatile memory or a non-volatile memory. If the memory 1320 is a volatile memory, Random Access Memory (RAM), Dynamic Random Access Memory (DRAM), Static Random Access Memory (SRAM), etc. may be used as the memory 1320 . If memory 1320 is a non-volatile memory, read-only memory (ROM), programmable read-only memory (PROM), electronically erasable read-only memory (EAROM), electronically erasable read-only memory ( EPROM), Electronically Erasable Programmable Read Only Memory (EEPROM), and flash memory (flash memory) etc. as the memory 1320 . The examples of memory 1320 as listed above are given by way of illustration only and are not intended to limit the invention.

The input/output interface 1330 can provide an interface in which input devices (not shown) such as a keyboard, mouse, and touch pad, etc., and output devices such as a display (not shown), etc., can be connected to the central processing unit 1310 to transmit and receive data.

The communication interface 1340 is configured to transmit and receive various types of data to/from a server or other user devices, and may be one of various devices capable of supporting wired or wireless communication. For example, the above-mentioned types of data related to digital behavior-based therapy may be received from individually available external servers via the communication interface 1340 .

As described above, digital instructions generated to treat mild cognitive impairment and/or Alzheimer's disease may be recorded in memory 1320 and processed at central processing unit 1310, such as to enable the digital instructions to be implemented as Modules for each function block executed.

Although all components of the embodiments of the present invention are described as being combined and operating together, the present invention is not necessarily limited to the embodiments of the present invention. That is, those components can be selectively combined and operated within the scope of the object of the present invention.

The terms "comprising" and/or "comprising" used above specify the presence of said features, integers, steps, operations, elements, components, and/or groups thereof, but do not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof. All terms used herein, including technical and scientific terms, may have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. Predefined commonly used terms can have the same or similar meanings as the contextual meanings of related technologies, and will not be interpreted in ideal or overly formal meanings unless the context clearly indicates otherwise.

While the invention has been shown and described with reference to certain exemplary embodiments thereof, those skilled in the art to which this invention pertains will understand that, without departing from the spirit and scope of the invention as defined by the appended claims, those skilled in the art will understand that , in which various changes in form and detail can be made. In other words, the embodiments disclosed in the present invention are not intended to limit the present invention, but are for illustration, and the exemplary embodiments do not limit the scope of the technical idea of the present invention. The scope of protection of the present invention should be based on the scope of the appended patent application, and all technical ideas within the same scope should be inferred to fall within the scope of rights of the present invention.

Although features and elements are described above in particular combinations, one of ordinary skill in the art to which this invention pertains will appreciate that each feature or element can be used alone or in any combination with other features and elements. In addition, the methods described herein can be embodied in a computer program, software, or firmware embodied in a computer-readable medium for execution by a computer or a processor. Examples of computer-readable media include electronic signals (emitted over wired or wireless connections) and computer-readable storage media. Examples of computer-readable storage media include, but are not limited to, read-only memory (ROM), random-access memory (RAM), scratchpad, cache memory, semiconductor memory devices, magnetic media such as internal hard disks, and Removable disks, magneto-optical media, and optical media such as CD-ROM disks and digital versatile disks (DVDs). A processor associated with software can be used to implement a radio frequency transceiver used in a wireless transmit/receive unit (WTRU), user equipment, terminal, base station, radio network controller (RNC), or any host.

100: device 105: Risk Factors 110: Nervous fluid factor 115: Physiological abnormalities 120: brain atrophy 125: Disease 130: Diagnosis 135: Patient Involvement 140: Balance Restoration of Neurofluid Factors 145: Healing effect 200: device 216: wireless interface 218: Processor 220: Transceiver 222: Transmitting/receiving components 224: Horn/microphone 226: small keyboard 228:Display/Touchpad 230: non-removable memory 232: Removable memory 234: power supply 236:GPS chipset 238:Peripheral equipment 500:Module 505:Nervous fluid factor 510: Hypothetical parameters 550: Basic factor 555:Medical information 560: Digital Healing Literacy or Comprehension 810: step 820: step 830: step 840: step 910: step 920: step 930: step 940: step 1010: step 1020: Steps 1030: step 1040: step 1050: step 1100: step 1110:step 1120: Step 1130: Step 1140: Step 1150: step 1210: step 1220: step 1230: step 1240: step 1250: step 1310: CPU 1320: Memory 1330: input/output interface 1340: communication interface

A more detailed understanding can be obtained from the following description, which is given by way of example in conjunction with the accompanying drawings. Figure 1A is a systematic diagram illustrating an exemplary mechanism of action (MOA) for Alzheimer's disease. Figure IB is a systematic diagram illustrating an exemplary treatment procedure based on the treatment hypothesis of treating mild cognitive impairment and Alzheimer's disease or inhibiting the development of mild cognitive impairment and Alzheimer's disease. Figure 1C is a system diagram illustrating another exemplary therapeutic procedure based on a user device for treating or inhibiting the progression of mild cognitive impairment and Alzheimer's disease. Figure 2 is a diagram illustrating an exemplary device that can be used to treat mild cognitive impairment and Alzheimer's disease. Figure 3 is a diagram illustrating exemplary input and output cycles of a user device for treating or inhibiting the progression of mild cognitive impairment and Alzheimer's disease. Figure 4 is a diagram illustrating an exemplary feedback loop for treating or inhibiting the development of mild cognitive impairment and Alzheimer's disease. FIG. 5A is a diagram illustrating an exemplary module for implementing digital therapy for treating or inhibiting the progression of mild cognitive impairment and Alzheimer's disease. Figure 5B is a diagram illustrating exemplary contextual factors supporting a user device for treating or inhibiting the progression of mild cognitive impairment and Alzheimer's disease. Figure 6A is a diagram illustrating an exemplary method of specifying a patient-specific prescription. Figure 6B is a diagram illustrating an exemplary method of specifying a patient-specific digital prescription. FIG. 7A is a diagram illustrating an exemplary digital indicator for setting an execution environment. FIG. 7B is a diagram illustrating an exemplary digital indication of a lifestyle module. FIG. 7C is a diagram illustrating an exemplary digital indication of a memory/learning module. FIG. 7D is a diagram illustrating an exemplary digital indication of a motion module. FIG. 7E is a diagram illustrating an exemplary digital indication of a positive/achievement module. Figure 8 is a diagram illustrating an exemplary procedure for using a digital application for treating or inhibiting the progression of mild cognitive impairment and Alzheimer's disease. Figure 9 is a diagram illustrating an exemplary procedure for generating digital instructions to treat or inhibit the progression of mild cognitive impairment and Alzheimer's disease. FIG. 10 is a diagram illustrating an exemplary procedure for repeatedly performing digital instructions based on feedback about treating or inhibiting the development of MCI and Alzheimer's disease. FIG. 11 is a diagram illustrating another exemplary procedure for repeatedly performing digital instructions based on feedback about treating or inhibiting the development of MCI and Alzheimer's disease. Figure 12 is a diagram illustrating an exemplary procedure for treating a patient with mild cognitive impairment or dementia by digital therapy. FIG. 13 is a diagram illustrating an exemplary hardware configuration of a user device for treating mild cognitive impairment and Alzheimer's disease or inhibiting the progression of mild cognitive impairment and Alzheimer's disease.

130: Diagnosis

135: Patient Involvement

140: Balance Restoration of Neurofluid Factors

145: Healing effect

Claims (20)

A method of treating a patient with mild cognitive impairment (MCI) or dementia by one or more digital therapies for treating a patient with mild cognitive impairment or dementia, the method comprising : determining whether the patient has the mild cognitive impairment or the dementia based on one or more symptoms of the mild cognitive impairment or the dementia; and Where the patient has been diagnosed with the mild cognitive impairment or the dementia, administering the one or more digital therapies to the patient to improve the mild cognitive impairment or the dementia causing the patient Multiple nerve fluid factors of the disease; wherein the one or more digital therapies include one or more digital instructions generated based on the neurofluids caused by the patient's performance of the one or more digital instructions At least one of the neurofluid factors is altered to treat an imbalance of at least one of the neurofluid factors. The method as described in claim 1, wherein the nerve fluid factors include sex steroid hormones, insulin-like growth factor-2 (insulin-like growth factor -2, IGF-2), β-catenin in Wnt signal transduction, Bcl-2-associated apoptotic gene 1 (Bcl-2-associated athanogene 1, BAG1), cyclic adenosine monophosphate response element-binding protein (cAMP response element-binding protein, CREB), multiple inflammatory factors, multiple corticosteroids , and at least one of a plurality of neurohormones. The method of claim 2, wherein the corticosteroids comprise cortisol and glucocorticoids, and wherein the neurohormones comprise dopamine, norepinephrine, and somatostatin. The method of claim 1, wherein the one or more digital indications include at least one of setting an execution environment, changing a life style, learning, exercising, affirming, and achieving a task. The method as described in claim 4, wherein the at least one imbalance of these nerve fluid factors includes sex steroid hormone imbalance, IGF-2 reduction, β-catenin degradation, BAG1 inactivation, CREB inactivation, inflammatory factor increase, At least one of increased corticosteroids, and decreased neurohormones. The method of claim 5, wherein the at least one neurofluid change in the patient comprises at least one of neurogenesis, anti-inflammation, anti-stress, and anti-depression in the patient's hippocampus. The method of claim 6, wherein at least one of the setting execution environment, the changing lifestyle, and the learning is related to the neurogenesis in the patient's hippocampus to treat the sex steroid hormone imbalance, the At least one of IGF-2 reduction, the β-catenin degradation, the BAG1 inactivation, and the CREB inactivation. The method of claim 6, wherein at least one of the setting execution environment and the learning is related to the stress resistance to treat the corticosteroid increase. The method according to claim 6, wherein the exercise is related to the anti-inflammation to treat the increase of the inflammatory factors. The method of claim 6, wherein at least one of the setting execution environment, the affirmation, and the achievement task is related to the antidepressant to treat the neurohormonal decrease. The method as described in Claim 1, further comprising: receiving results of the patient's performance of the one or more digital indicators repeated a predetermined number of times by the patient; and Based on the result, one or more digital instructions are generated to treat at least one imbalance of the neurofluid factors. The method of claim 1, wherein the one or more digital treatments are performed by a wireless transmit/receive unit (WTRU). A method of treating a case of mild cognitive impairment (MCI) or dementia by one or more digital therapies for treating a case of mild cognitive impairment or dementia, the method comprising : The one or more digital treatments administered by the case to improve the plurality of neurofluidic factors causing the mild cognitive impairment or the dementia in the case, wherein the one or more digital treatments include one or more a first digital instruction, the one or more first digital instructions being generated to treat the neurofluidic changes in at least one of the neurofluidic factors resulting from the execution of the one or more digital instructions At least one of the factors is out of balance. The method as described in claim 13, wherein the nerve fluid factors include sex steroid hormones, insulin-like growth factor-2 (insulin-like growth factor-2, IGF-2), β-catenin in Wnt signal transduction, Bcl-2-associated apoptotic gene 1 (Bcl-2-associated athanogene 1, BAG1), cyclic adenosine monophosphate response element-binding protein (cAMP response element-binding protein, CREB), multiple inflammatory factors, multiple corticosteroids , and at least one of a plurality of neurohormones. The method as recited in claim 13, wherein the one or more first digital indications include at least one of setting an execution environment, changing a life style, learning, exercising, affirming, and achieving a task. The method as described in claim 13, wherein the at least one imbalance of the nerve fluid factors comprises sex steroid hormone imbalance, IGF-2 reduction, β-catenin degradation, BAG1 inactivation, CREB inactivation, inflammatory factor increase, At least one of an increase in corticosteroids, and a decrease in neurohormones, and wherein the at least one neurofluid change in the subject comprises at least one of neurogenesis, anti-inflammation, anti-stress, and anti-depression in the subject's hippocampus. The method as described in Claim 13, further comprising: receiving one or more second digital instructions from the case as a result of executing the one or more first digital instructions; and The one or more second digital instructions are executed based on the result to treat at least one imbalance of the neurohumoral factors. A device used by individuals with mild cognitive impairment (MCI) or dementia, including: A processor configured to generate one or more digital treatments to improve a plurality of neurofluidic factors causing a case of mild cognitive impairment or dementia, wherein the one or more digital treatments include one or more a digital instruction, the one or more digital instructions produced to treat the neurofluidic fluid based on a change in at least one of the neurofluidic factors caused by the individual's performance of the one or more digital instructions At least one of the factors is out of balance. The apparatus of claim 18, wherein the processor is further configured to generate one or more second digital indicators based on the subject's performance with respect to the one or more digital indicators to treat the neurological conditions of the subject At least one of the fluid factors is out of balance. The device as described in Claim 18, further comprising: a transmitter configured to transmit results of the case's performance with respect to the one or more digital indicators to another device of a medical entity; and a receiver configured to receive one or more second digital therapies from the other device, comprising one or more second digital indications generated based on the result for treating at least one imbalance of the neurofluidic factors .

Images