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FDA Success Stories, CDE Recommendations: How Does MIDD Accelerate New Drug R&D?

 Last Update: 2022-11-01
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With the encouragement of innovative drug policies and the normalization of generic drug procurement, in less than 10 years, domestic traditional pharmaceutical companies have transformed and upgraded, emerging innovative pharmaceutical companies have sprung up vigorously, and more and more
companies have joined the innovative drug competition track.

How to make drug creation easy? MIDD solves this problem
very well.

MIDD (model-guided drug development) can further improve the success rate of research and development on the basis of traditional experience, and there have been many successful cases (including the well-known osimertinib and pembrolizumab), and in recent years, CDE is also encouraging recommendations, which is an indispensable and important means
for future drug research and development.
At present, the leading technology-based innovation companies include XtalPi Technology, Wangshi Wisdom, Fanmo Valley, Chuangteng Technology, Tigermed Pharmaceutical, Amador Biologics, etc.
, please see below
.

25% of Class 1 innovative drugs are in use, what is MIDD?

MIDD, or "model-guided drug discovery" (slightly different from the earlier MBDD ---- model-based drug discovery), uses modeling and simulation techniques to integrate and quantify information such as physiology, pharmacology and disease processes to guide new drug development and decision-making
.

The application of modeling and simulation in drug discovery and its full life cycle management involves multiple aspects, covering all stages from non-clinical to clinical research and post-marketing clinical re-evaluation, as shown
in the figure below.

Figure 1 Application diagram of modeling and simulation technology in the drug development life cycle Image source: CDE "Model-Guided Drug Discovery Technical Guidelines"

the drug discovery phase, which can be used to discover and demonstrate the ability of the target to bind to the drug candidate; In the preclinical development stage, some in vivo and in vitro correlations can be done to evaluate safety and efficacy and further calculate the FIH dose; In the clinical development stage, it can be used to optimize the dosing regimen (such as dose escalation design, dosing interval, etc.
), recommend doses for subsequent clinical trials and provide supporting evidence for instructions, and reduce the need to carry out confirmatory clinical studies of the same dose as much
as possible.

According to research statistics, about one-quarter of the Class 1 innovative drugs approved by the NMPA in 2018 used MIDD-related research methods, and another one-third of the varieties were required to carry out MIDD-related analysis in post-marketing studies; Among the new anti-tumor drugs newly approved by the NMPA in 2019, about 70% have carried out research on Pop PK, and the utilization rate of imported varieties is significantly higher than that of domestic varieties
.

What are the relevant guidelines issued by CDE?

In August 2020, CDE issued a notice on publicly soliciting comments on the Technical Guidelines for Model-Guided Drug Development (Draft for Comments); At the end of 2020, CDE issued the "Technical Guidelines for Model-Guided Drug R&D", which was officially implemented
.

Figure 2 CDE official website released "Model Guided Drug Development Technical Guidelines" Image source: CDE official website

In July 2022, CDE released a questionnaire on the practice of "model-guided drug research and development (MIDD)" in new drug research and development enterprises, which emphasized that "clinical pharmacology research is of great significance to new drug research and development" and "the application of modeling and simulation technology is becoming more and more extensive, which plays an important role in improving the efficiency of new drug research and development and guiding decision-making", that is to say, model-guided drug research and development has a relatively large
weight in the development of innovative drugs.
Some of the relevant guidelines are shown
in the table below.

Table 1 A partial list of model-related guidelines

FDA Success Stories, K Drug, 9291

Studies have confirmed that from the FDA's published innovative drug review report, almost all of the varieties submitted for new drug registration applications contain MIDD research content, such as 9291 (osimertinib) and K drug (pembrolizumab).

➣ 9291 (osimertinib)

Osimertinib is mainly metabolized by the liver (CYP3A4/5 enzyme), renal clearance accounts for a small proportion, in vitro transporter experimental data show that osimertinib is a breast cancer resistance protein inhibitor, suggesting that when the drug is combined with CYP3A enzyme substrate, inducer, inhibitor or BCRP substrate, DDI
may occur.
Therefore, DDI studies
of osimertinib and itraconazole (strong inhibitor of CYP3A), rifampicin (strong inducer of CYP3A), simvastatin (CYP3A substrate) and rosuvastatin (BCRP substrate) were carried out.
In the above process, Simcyp software (PBPK modeling and simulation platform) is used to establish a PB PK-DDI model, and finally based on the DDI prediction and simulation research strategy of the PBPK model, make full use of in vitro and partial clinical trial data, and exempt from unnecessary clinical trials
.

➣ K medicine (pembrolizumab)

In the early stage of FIH, by establishing the Imax model, it was preliminarily estimated that 1mg/kg administration could achieve in vitro target receptor saturation, so as to determine the maximum recommended starting dose of FIH test and start the KEYNOTE‐001 study
.

Using preclinical mouse experimental data, a pembrolizumab PK/PD tumor growth inhibition model was constructed and extrapolated to humans, and the results showed that when the dose was 2mg/kg, the receptor occupancy rate of pembrolizumab exceeded 95%, and the probability of achieving tumor volume reduction greater than 30% reached the ping value, suggesting that 2mg/kg can be used as an effective dose for clinical trials, and combined with circulation for modeling and simulation, in subsequent clinical studies, the dose level (2mg/ kg) was used in larger randomized controlled trials
in patients with advanced melanoma and NSCLC.

PopPK model analysis showed that the PK curve of pembrolizumab was consistent with classical therapeutic monoclonal antibodies, showing limited volume of distribution, low clearance and low variability, and internal and extrinsic factors had no clinically significant effect
on the exposure of pembrolizumab.

After incorporating the blood concentration data of some clinical trials into the model and refitting, simulating the systemic exposure of fixed-dose dosing, and comparing with the weight-based dosing regimen, the results showed that the PK variability of the two dosing regimens was comparable, and further confirmed the accuracy of the regimen predicted based on the PopPK model, and finally the FDA approved the application
for pembrolizumab to change from bodyweight-based administration to fixed-dose administration.

In addition to the above representative cases, the FDA has many other classic cases, such as:

1) Nesiritide, in 1999, the FDA issued a letter of non-approval, suggesting that the applicant optimize the dose, minimize the expected effect, and quickly achieve the expected effect, through the E.
R model, finally simulate the dose that can achieve the best benefit/risk, the applicant chose the dose method for clinical trials, the test results confirmed to be similar to the simulation results, the applicant submitted the test results to the FDA, the FDA approved the drug for the treatment of acute heart failure in 2001
。

1）Nesiritide

2) Zoledronicacid, FDA through modeling analysis showed that drug exposure is associated with nephrotoxicity, and after discussion with the applicant, it is recommended that patients with mild to moderate renal insufficiency adjust the dose according to AUC and add this recommendation to the
instructions.

2）Zoledronicacid

Recent cases of MIDD literature in academia

In addition to the above successful cases based on regulation, there are also many good research results in the literature, and the examples are as follows
.

➣ Population pharmacokinetic model

Structural models typically include absorption, disposal models, and pharmacodynamic models
.
Common absorption models include zero-level, first-level, mixed model, gradient absorption model and special model; The disposal model refers to the atrioventricular model in traditional pharmacokinetics, including one-, second-, three-chamber and other atrioventricular models; Pharmacodynamic models include linear models or sigmoid models
.
The most important parameters of the pharmacodynamic model include the maximum potency of the drug (Emax) and the concentration of the drug (EC50)
when half the maximum efficacy is reached.

Example 1: Model supports evaluation of preclinical pharmacokinetics of Lorlatinib

Journal of Pharmaceutical Sciences (2022), there are studies by using a series of transgenic mice to avoid the influence of transporters and enzymes on the pharmacokinetics of the drug, and then taking Lorlatinib, measuring the corresponding PK data, and through the corresponding population pharmacokinetic modeling methods, it is finally inferred that Lorlatinib is mainly dissolved in the stomach of mice, and the absorption rate in the intestine will be reduced
。 The absorption curves submitted by Lorlatinib to the FDA used mixed models, and the final model fitting curves were much similar
.

Fig.
3 Fitting of Lorlatinib pharmacokinetic model Image source: Journal of Pharmaceutical Sciences (2022) 495-504

➣ Pharmacokinetic/pharmacodynamic models

PK-PD model is a comprehensive study of the kinetic process and pharmacodynamic quantitative index in vivo, and organically combines the relationship between time, drug concentration and drug effect described by pharmacokinetics and pharmacodynamics, which is helpful to understand more comprehensively and accurately the law
of drug effect changes with dose (concentration) and time.
The application scope of PK-PD model is very wide, and it can be applied to the screening of active drugs, the determination of phase I clinical maximum tolerance measurement, the study of the mechanism of action, clinical guidance of medication, optimization of dosing regimens, formulation evaluation, etc
.

Example 2: Prospective clinical validation of propofol PK-PD

Most of the existing clinical research models are from specific population data, strictly speaking, the use of these models is limited to these populations, and the more extensive propofol PK-PD model is carried out to prospectively test the model in children, adults, the elderly, and obese adult subjects receiving general anesthesia, and finally confirm that in clinical anesthesia, the PK-PD model of the study is overall better predictive (more inclined to population PK-PD).

Fig.
4 Relationship between target concentration and age in PK-PD model Image source: British Journal of Anaesthesia, 126 (2): 386-394 (2021)

➣ Physiology-based pharmacokinetic model

Physiopharmacokinetic (PBPK) models can mimic the chronological process
of drugs in various tissues and blood through the physicochemical properties of drugs and data obtained by in vitro tests.
In addition, the PK behavior of drugs in animals can be extrapolated between species to predict human PK.

The PBPK model takes into account the process factors that affect drug absorption, distribution and elimination, and describes the exposure of drugs in tissues and organs and their changes over
time.
Thus, the PBPK model allows early prediction of local organ tissue concentrations, which can be correlated with pharmacodynamic models to assess the response of any particular tissue.

Example 3: Study of the druggability of Danirixin free bases and various salts

Using the PBPK model to investigate the druggability of the free base and various salts of Danirixin (GSK1325756), which is currently in clinical research for the treatment of chronic obstructive pulmonary disease, the PBPK model confirmed a decrease in the bioavailability of the free base downstream of the presence of proton pump inhibitors (AUC decreased to 42%, Cmax decreased to 27%), while no equivalent reduction in PK exposure was observed for hydrobromide, and compared with free bases, Clinical studies of hydrobromate are supported by increased hydrobromate exposure (1.
32-fold increase in AUC and 1.
44-fold increase in Cmax
), the simulation results are consistent with the results of subsequent clinical trials, hydrobromide reduces the variability of drug exposure, and the exposure is not affected by the combination of proton pump inhibitors.

Fig.
5 Observed and predicted pharmacokinetic spectrum Image source: EJPB.
doi.
org/10.
1016/j.
ejpb.
2017.
03.
023

Domestic MIDD status: XtalPi, Fanmo Valley, Tigermed and Amador Biologics

In the past 10~20 years, a number of technology-based innovative companies have emerged in the domestic drug R&D industry, such as XtalPi Technology, which is deeply engaged in drug solid-state research and is known to the industry, and Wangshi Wisdom in the direction of AI small molecule drug research and development; The focus on model-guided drug research and development include Fanmo Valley, Thuangteng Technology, and some clinical CRO companies such as Tigermed and Amador Biologics
.

In addition to the above-mentioned technology-based companies with strong focus on technology, regulatory departments, hospitals, and universities have always published corresponding research, but the overall is still inclined to be academic; Companies that pay more attention to the specific implementation of projects are more in the early contact stage for model-guided drug research and development, and tend to cooperate, solve some problems, and preliminary research
in related fields.

Examples of enterprise users in Fanmo Valley include: Hutchison Whampoa, BeiGene, Dizhe Pharmaceutical, Hua Medicine Pharmaceutical, Haosen Pharmaceutical, Kelun Pharmaceutical, Luoxin Pharmaceutical, Huadong Pharmaceutical, Taiwan Zhonghuan, WuXi AppTec, HeXi Pharmaceutical, Hong Kong InSilico, Shengsu New Medicine, Kanglong Chemical, etc
.

Barriers to widespread use of MIDD

Although CDE has issued relevant guidelines, the level of recognition and recognition is still not high
.
At the same time, traditional drug research and development based on experience is still the mainstream of domestic new drug research and development, and capital still follows highly successful leaders
.

In addition, the landing of MIDD requires multidisciplinary and comprehensive talents based on awareness and technology, including quantitative clinical pharmacology, statistics, program engineering, data management, etc.
, and requires in-depth cooperation
with clinical PI.

Moreover, the existing models need to be constantly updated and evolved, and the research of the model is still in its early stages, and it is necessary to study the development and application of various models in depth.

Although facing layers of obstacles, it is imperative for MIDD to join the research of the whole life cycle of new drugs, and has been verified by a large number of successful cases, it is necessary to incorporate part of the planning work of MIDD before the start of clinical trials, or even when the drug candidate enters the development period, and continuously accumulate experience to bless
the success rate of new drugs from a computational point of view.

We will eventually make drug creation easy
.

Any job that can increase the probability of success in the research and development of new drugs, pharmaceutical people cannot easily give up.
.
.

References:

References: References:

1.
CDE.
Technical Guidelines for Model-Guided Drug Discovery.
2020

2.
CDE.
Questionnaire on the practice of MIDD in new drug research and development enterprises.
2022

3.
Identification and characterisation of a salt form of Danirixin with reduced pharmacokinetic variability in patient populations.
doi.
org/10.
1016/j.
ejpb.
2017.
03.
023

4.
Prospective clinical validation of the Eleveld propofol pharmacokinetic-pharmacodynamic model in general anaesthesia.
British Journal of Anaesthesia, 126 (2): 386e394 (2021).

5.
Population Pharmacokinetic Modelling to Support the Evaluation of Preclinical Pharmacokinetic Experiments with Lorlatinib.
Journal of Pharmaceutical Sciences 111 (2022) 495−504.

6.
Physiologically-based modeling of monoclonal antibody pharmacokinetics in drug discovery and development.
doi.
org/10.
1016/j.
dmpk.
2018.
11.
002

7.
Analysis of the application of MIDD in clinical research of antitumor drugs.
Chinese Journal of Lung Cancer.
2022

8.
Population pharmacokinetic model establishment.
Chin J Clin Pharmacol.
2013

9.
Model-based drug discovery.
Chinese herbal medicine.
2011

10.
Application of model-guided drug development in new drug development.
Chin J Clin Pharmacol Ther 2020

11.
Model-Guided Drug Discovery: Development History and Application Thinking.
Chinese Journal of Clinical Pharmacology.
2021

12.
Application of physiological pharmacokinetic software simulation technology in drug development and evaluation.
Pharmaceutical Research.
2022

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