High-throughput ADME research in the new drug discovery phase

2020-10-14

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In the past ten years, the cycle of drug discovery and development has become longer and longer, and the cost of testing has increased. In Western countries, it takes 10 to 15 years to develop and market a new compound entity, and it costs more than US$800 million. Of the 10,000 new compound entities, 10 have entered the clinical phase of research, but only one drug candidate will eventually be marketed. Even drugs that are already on the market may be withdrawn from the market due to unacceptable adverse drug reactions. Therefore, the development of new drugs is a “high-risk, low-efficiency process.” For the development of innovative drugs, the process consists of 3 stages and 4 steps:

① Discovery, characteristics and evaluation of target sites (biological target stage);
② Discovery and optimization of lead compounds (drug discovery stage);
③ADMET (absorption, distribution, metabolism, excretion and toxicity), PK, PD research (drug discovery and development stage);
④Clinical trials (drug development stage).

High-throughput ADME research.jpg

In order to get more drugs on the market, two measures can be taken: one is to increase the number of compounds to be screened, which is restricted by various conditions, such as the limitations of funding, time, resources, and scale; the other is to increase the success rate of research and development, such as taking Reasonable drug design, ADMET research in the drug discovery stage, etc. Obviously, improving the success rate of R&D is more favored by R&D units. In a retrospective study conducted in 1990, it was found that about 40% of candidate drugs that failed in the clinical stage were caused by pharmacokinetic reasons. The pharmaceutical industry has realized that for a candidate drug with target site activity and selectivity, if its ADME properties do not meet the drug-like requirements, the candidate drug cannot eventually become a drug. For this reason, new drug researchers advance the ADME research in the late stage of drug discovery to the early stage of drug discovery, so that compounds that do not meet the drug-like properties are eliminated as soon as possible, and the success rate of research and development is improved. After decades of research, statistics in 2000 showed that among the drugs that failed in the clinical stage, the proportion of drugs that were eliminated due to PK has dropped significantly.
During the drug discovery stage, ADME research is faced with the problem of a large variety of compounds to be tested (due to the development of combinatorial chemistry and parallel synthesis technology), many items to be tested, and a small amount of each compound. This requires minimization, automation, and high-throughput improvements to existing testing methods to match the testing speed of compounds with the synthesis speed of combinatorial chemistry. In addition, in the design of the experimental process, a parallel operation method is adopted to speed up the development of new drugs, and related research is carried out at the same time. In the past, serial research was often adopted, that is, one test was completed before the next one was performed, which was very inefficient. The future method is to carry out virtual library screening combined with parallel operations, and use the established structure-activity relationship to screen virtual compound libraries without compound synthesis, thereby greatly saving resources and accelerating the speed of drug discovery.
In the drug development stage, ADME research carried out includes: in silico or computational method; in vitro method; in vivo method. Each of these three methods has its advantages and disadvantages.

The use of high-throughput screening technology can quickly identify lead compounds. However, compound libraries constructed through combinatorial chemistry have the problem of poor structural diversity, which reduces the success rate of compound development; secondly, the poor drug-like properties of the compounds make a large number of Compounds were eliminated during ADME screening, which increased experimental costs. In the past 20 years, although new technologies in the drug discovery stage have emerged one after another, there has been no substantial increase in the number of new compound entities on the market each year. In addition, most of the current established high-throughput determination methods are related to the structure of the tested compounds, and do not have complete versatility.

ADME research

Virtual screening method
Although many in vivo and in vitro miniaturized, simplified, and automated experimental methods have been developed, the analysis time, labor intensity, and the number of processed compounds have been greatly improved, but the experimental methods are still considered slow , Expensive, and need to carry out the synthesis of candidate compounds. The virtual screening method can be seen as an alternative method for predicting the ADME characteristics of candidate compounds. This method has high throughput or ultra-high throughput.
(1) Prediction of intestinal absorption
Oral absorption is related to the solubility and dissociation of the drug in the contents of the gastrointestinal tract, and the ability to cross the gastrointestinal cell membrane. Therefore, the physical and chemical properties of the compound are an important determinant of the permeability of the small intestine. Methods to improve oral absorption of drugs include:
Based on Lipinski’s role of five method. In the structure of the compound, N and O atoms are regarded as hydrogen bond acceptors, and N-H and O-H groups are regarded as hydrogen bond donors. Calculate the alcohol-water partition coefficient ClgP by software. If a compound meets the following two or more conditions:
●Number of hydrogen bond donors>5
●Number of hydrogen bond acceptors>10
●ClgP>5
●MW>500Da
Then this compound will be given a development warning sign, and future druggability is questionable. This method is not suitable for prediction of oral drugs with active transport mechanism.
The second method also uses Lipinski’s five rules, but combines the lipophilicity and molecular size information to determine the passive absorption of the compound during oral absorption. The intrinsic lipophilicity of the compound (considering the degree of dissociation at physiological pH) ClgD is plotted against the calculated molecular refraction (CMR), a parameter for determining molecular size. The compound is divided into 4 quadrants. In the first and third quadrants, the compound has appropriate lipophilicity and can be transported across the membrane; in the second quadrant, the compound has a small molecule and strong hydrophilicity and can be absorbed through the intercellular space. ; And the compound in the fourth quadrant has a large molecular weight and strong hydrophilicity, making it difficult to absorb the compound across the membrane. According to the different quadrants of the compound, the permeability of the compound can be predicted.
The molecular polar surface area (PSA) is used as a predictive method for drug absorption. Studies have shown that PSA and molecular weight are correlated with the apparent permeability index obtained by Caco-2 cells.
(2) Prediction of the permeability of the blood-brain barrier (BBB)
In the discovery phase of new drugs, drugs that act on the central nervous system require the drug to have a certain BBB permeability, and for drugs that act on the periphery, the lower the ability to penetrate the BBB, the better, in order to reduce the central nervous system of the drug Adverse reactions of the system. To this end, it is necessary to predict the ability of candidate drugs to penetrate the BBB.
Van de Waterbeemd gave a BBB permeability prediction method. MW<450 da="" and="" psa="">90Å are considered to have BBB permeability. But this method does not consider the influence of P-gp.
(3) Prediction of metabolic stability
To obtain the best bioavailability, proper absorption and metabolic stability are required. It is currently known that the fat solubility, molecular size and shape, functional groups and locations of compounds affect the stability of drugs in vivo. The reason can be attributed to whether the structure of the compound can enter the P450 binding catalytic site. Models in this area are still in the early stages of development.
According to reports, the predictive ability of the current virtual screening method is between 60% and 90%, and the empirical model used is related to the compound training set used. In the future, more compounds with different structures need to be used to verify the model. It is also necessary to clarify the mechanism of ADME in vivo and establish a mechanism model for prediction.
In vitro methods
In the past 10 years, in vitro methods have been widely used to determine permeability, bioavailability, metabolic stability, drug interactions, and drug physical and chemical parameters. The advantages of the in vitro method are that one can use miniaturization, automation and other means to establish high-throughput or medium-throughput models; secondly, it can use tissue and cell components from humans for research to eliminate species differences between humans and animals , Improve the success rate of drug development. However, in vitro studies lack the influencing factors such as blood flow, biochemical factors, and multiple transport proteins that exist in in vivo studies. In addition, the organic solvents used in the compound preparation process may mask the solubility of drugs in the body and affect the activity of drug metabolizing enzymes.
(1) Evaluation model of intestinal absorption
Drugs enter the body’s circulation and need to pass through the low pH environment of the stomach after oral administration, enter the duodenum and small intestine, and be absorbed into the blood in the small intestinal epithelial cells after dissolution and release. There are four ways of intestinal epithelial cell absorption: trans-cell uptake, intercellular permeation, carrier-mediated uptake and carrier-mediated outflow. Several systems have been developed to evaluate the oral absorption of drugs. Common methods include Caco-2 cell line, MDCK cell line, and PAMPA artificial membrane method. Among them, PAMPA is an absorption evaluation model based on passive diffusion, which is a high-throughput research method, while the Caco-2 cell line and MDCK cell line are low-throughput methods.
(2) Studies on metabolic stability
After the drug enters the body as a foreign substance, it will undergo biotransformation caused by drug metabolizing enzymes. Although P450 isoenzymes sometimes found in the epithelial cells of the small intestine, such as CYP3A4, can cause the first pass effect of drugs, the liver is the largest metabolic organ in the body. There are phase I metabolic enzymes such as P450 enzymes, non-P450 enzymes such as esterase, flavin-dependent monooxidase, monoamine oxidase, etc. in the liver; phase II metabolic enzymes such as glucuronyl transferase, sulfotransferase, etc. Among the above-mentioned enzymes, P450 enzyme is the main metabolic enzyme in the body. Among P450 isoenzymes, CYP1A2, CYP2A6, CYF2B1, CYP2C9, CYP2C19, CYP2D6, CYP2E1, CYP3A4 are enzymes related to drug metabolism. Among them, CYP3A4 is the enzyme with the largest content of P450 enzymes and the highest proportion of metabolizing drugs. To 50% of the total number of metabolized drugs. Metabolic stability is an important feature of drugs, and metabolically unstable drugs require frequent administration to maintain the therapeutic concentration of the drug.
Due to species differences in metabolism, the results obtained by using tissues and cells from the human body in the drug development phase are closer to clinical results. The in vitro systems used in the study of enzyme metabolism stability are mainly human liver microsomes and hepatocytes. It is currently known that the P450 enzymes contained in liver microsomes and their ratios are close to those in liver tissues. Liver microsomes are easy to store and can be used for high-throughput enzyme stability studies. Liver cells contain a complete enzyme system and do not need to add cofactors, but liver cells have a short storage time and limited sources.
(3) Determination of physical and chemical parameters
In the drug discovery stage, the physical and chemical parameters of candidate compounds, such as solubility, dissociation constant, lipophilicity, etc., affect the absorption, distribution, metabolism and excretion of the drug, so it is necessary to determine these physical and chemical parameters in the drug discovery stage. A high-throughput method for determining physical and chemical parameters has been developed.
Solubility
The classic solubility determination method is the shake flask method. Due to the need to reach saturation during the determination, the test cycle is long (up to 7 days) and the amount of drugs used is large, which is not suitable for high-throughput research. People later developed a variety of high-throughput methods for measuring solubility. The turbidimetric method and UV measurement method are commonly used in the drug discovery stage. These two methods can measure the solubility of hundreds of compounds every day.
Lipophilicity
Lipophilicity means the affinity of a compound or some of its groups to a lipophilic environment. It is generally expressed by the distribution behavior of the compound in the two phases, such as the n-octanol-water partition coefficient. Lipophilicity can be used to predict the permeability and metabolic stability of drugs. Generally, the stronger the lipophilicity of the compound (eg lgD>5), the stronger the membrane permeability of the compound, and the easier it is to be metabolized by liver drug enzymes in the body; while the hydrophilic compound (1gD<0), then It does not easily penetrate cell membranes and is easily excreted by the kidneys in the body. A suitable drug, with a lipophilicity of lgD between 0 and 3, exhibits a balance between solubility and lipophilicity in the body. The commonly used measurement method is the shake flask method. The principle is to dissolve the test compound in a buffer and add an immiscible solvent. After reaching equilibrium, the two phases are separated, and the pH of the water phase is measured, and the compound is in the water phase. And the concentration of the organic phase. The calculated fat solubility is the partition coefficient in a partially dissociated state at a specific pH, expressed by lgD. If a compound non-dissociation system such as a neutral system is used, the calculated result is lgP. The high-throughput determination method of fat solubility is HPLC method, which determines the partition coefficient between the mobile phase and the non-polar stationary phase (such as C. Bonded phase) (expressed by retention time); other methods have 96 wells The plate incorporates a method of UV absorption measurement.
Dissociation degree
The dissociation degree of a compound can help understand the dissociation degree of the compound under different pH conditions. When pH=pKa, half of the compound is in a dissociated state, generally in a neutral state. The gastrointestinal tract and the biological internal environment are in different pH states, which affect the dissociation state of the drug, thereby affecting the solubility and lipophilicity of the drug, and further affecting the absorption of the drug and the binding of the protein. The conventional method for determining pKa in the past is the potentiometric titration method, which has a low throughput and requires a large amount of samples. It can only measure 10 compounds a day. Other methods include capillary electrophoresis, which requires a small amount of samples. But the flux is only 10 compounds per day. The high-throughput method is mainly spectral gradient analysis (SGA), which can use 96-well plates, and the throughput can reach 240 compounds per day.
In order to determine the interaction potential between drugs, the pharmaceutical industry mainly conducts experiments in accordance with the following methods.

(4) Drug interaction research
There have been many examples of drug withdrawal due to the interaction caused by pharmacokinetics, and there are two main mechanisms for this situation: enzyme inhibition and enzyme induction.

Determination of metabolic enzymes
Identify the key enzymes responsible for the metabolism of the drug in the body, and evaluate the interaction potential between the test drug and the inhibitor or inducer. For example, if a drug is mainly metabolized by CPY3A4, the drug may interact with CYP3A4 inhibitors such as ketoconazole, erythromycin, itraconazole, or inducers such as rifampin and phenytoin. When conducting drug interaction potential studies, the extracted liver microsomes, recombinantly expressed liver microsomes, and liver cells can be used. The recombinant expression of liver microsomes can be used to determine drug metabolism enzymes; the combination of liver microsomes and a P450 isoenzyme inhibitor can also be used to speculate drug metabolism enzymes; the combination of human liver cells and inhibitors can be used for drug metabolism pathways The determination is because liver cells include phase II metabolic enzymes in addition to phase I metabolic enzymes.
Evaluate the inhibitory potential of candidate compounds on key drug metabolizing enzymes
If a compound is an inhibitor of a drug metabolizing enzyme, it can interact with the drug substrate of the enzyme. The use of liver microsomes and special substrates in the research can be used to study the potential of enzyme inhibition, and the drug interaction potential can be judged based on the calculated IC50 or Ki value. It is also possible to use recombinantly expressed liver microsomes and liver cells for research. This research can be conducted in a high-throughput manner.
Induction potential
If a drug can induce liver cells to overexpress a certain metabolic enzyme, the drug can interact with the substrate of the drug-metabolizing enzyme. This study can only be carried out using live primary hepatocytes, and the experiment needs to last for 2-4 days. This method is a low-throughput method. Another method is to use XPR-reporter cell line for research, which can increase the throughput of research. It is known that XPR is the receptor of CYP3A4 inducer, and the combination of the drug with XRP will cause the activation of the linked reporter gene, which indicates that the drug is an inducer of CYP3A4.
In addition, what needs attention is the drug interaction caused by the drug transporter; the mechanism of inhibition should also be analyzed to distinguish whether it is competitive enzyme inhibition or mechanism-dependent enzyme inhibition. It has been reported that the probability of drug interactions caused by mechanism-dependent enzyme inhibition is higher. In addition, the inhibitory effect of phase II metabolic enzymes also needs attention.
In vivo methods
In the drug discovery stage, in vivo animal research is very different from the in vivo research in the drug development stage in terms of dosage, blood sampling point, and number of animals. At this stage, the purpose of in vivo research is mainly for the optimization of lead compounds, combined with in vitro research results to make recommendations for further research on candidate compounds. In vivo research is a low-throughput, time-consuming, large amount of sample, and uneconomical research method. However, in vivo research has influencing factors such as blood flow and various factors that are not available in in vitro research, and is indispensable in new drug research. One item. In in vivo research, two methods are generally adopted to increase throughput: increase the analysis speed and reduce the number of samples.
(1) Improve sample analysis speed
In in vivo studies, there are a large number of samples to be measured. Increasing test speed is the most common way to increase throughput. Sample analysis is generally HPLC method and LC-MS/MS method. Due to the different structures of the compounds to be analyzed, the established method requires a certain degree of sensitivity and specificity. Due to the long method establishment time and the many sample processing steps in HPLC, the requirements for high-throughput testing cannot be concealed. LC-MS/MS is used more and more in sample analysis due to its high sensitivity, good specificity, and simple sample processing (protein precipitation for biological samples). The disadvantage of this method is the influence of matrix effect. Another way to increase the test speed is to use an on-line solid phase extraction (SPE) method to automatically process samples. The disadvantage of this method is that the method is still cumbersome to establish and the analysis time is long.
Another way to improve throughput is to perform turbulent flow chromatography, which can use serum and urine samples for analysis without processing. Other methods to increase the analysis speed are parallel LC-MS/MS analysis using the MUXTM system. Generally, 4 chromatographic columns can be used, and the effluent of each column is introduced into the ionization chamber of MS/MS in turn. Compared with LC-MS/MS using one column, the analysis speed of this method can be increased by nearly 4 times. In terms of chromatographic columns, short chromatographic columns with fine particles can be used to shorten the analysis time. Liquid chromatography using this column is called negative separation liquid chromatography. Such as the use of fine-grained short columns (2.1mm×20mm, 3 μm or finer packing), universal rapid gradient (organic phase from 5% to 95% within 2 minutes, fluidity containing 0.035% to 0.05% trifluoroacetic acid or 0.1% formic acid or 10 mmol/L ammonium acetate), high flow rate (1-5 ml/min), etc., these operations can make each sample analysis time only 30s.
(2) Reduce the number of samples
In in vivo studies, the number of samples can be reduced by cassette dosing. Several drugs can be used in combination. Once a sample is taken, the concentration of several drugs can be determined simultaneously by LC-MS/MS. The most controversial method is the possible drug interactions; another method is to mix several samples containing different drugs and then measure them together. You can also mix equal amounts of blood samples at different time points after administration to roughly estimate the drug in the body AUC.
What needs to be emphasized is that a data processing system should be established to match the measurement speed. Through the use of different software, the data obtained can generate reports that can be easily identified by decision makers.