Multi-technology combined medication analysis platform for oligonucleotide drugs

Abstract

The invention discloses a multi-technology combined medication analysis platform of an oligonucleotide drug, which relates to the technical field of drug analysis and is technically characterized by comprising an oligonucleotide drug delivery technology module, a liposome, a polymer nanoparticle or an exosome is selected as a delivery carrier, the surface of the delivery carrier is modified with hydrophilic polyethylene glycol or a targeting ligand, and the oligonucleotide drug delivery technology module is connected with the oligonucleotide drug delivery module. The performance of the material is represented by dynamic light scattering and a transmission electron microscope; the multi-technology platform analysis module integrates RT-qPCR, LC-FL, LC-MS / MS and LC-HRMS technologies, is respectively used for target gene expression quantification, drug distribution tracking, drug principal component quantification and metabolite structure analysis, establishes a cross validation rule, and requires a correlation coefficient R2gt of an LC-MS / MS quantitative result and RT-qPCR expression data; 0.95%, 0.95%; the pharmacokinetic evaluation module constructs a PBPK model to predict human pharmacokinetic parameters, and draws a drug metabolism network diagram in combination with an LC-HRMS metabolite identification result; by integrating various advanced analysis technologies, the problems of low sensitivity, poor specificity and difficult metabolite analysis in the prior art are solved.

Description

Technical Field

[0001] The present invention relates to the technical field of drug analysis, and in particular to a multi-technology combined pharmacokinetic analysis platform for oligonucleotide drugs. Background Art

[0002] Oligonucleotide drugs, as a new generation of biopharmaceuticals, show great potential in the treatment of genetic diseases, tumors, and metabolic diseases due to their high specificity and targeting. However, their small molecular weight, strong polarity, and easy degradation lead to the following technical bottlenecks in bioanalysis: First, the sensitivity is insufficient: traditional analytical methods are difficult to meet the quantitative requirements of low-concentration oligonucleotide drugs; Nonspecific binding interference: Drug molecules are prone to nonspecific adsorption with containers, reagents or biological matrix components, affecting detection accuracy; Difficulty in chromatographic retention: Oligonucleotide drugs have short retention time on chromatographic columns and poor separation effect; Metabolite analysis is complex: drugs and their metabolites have high structural similarity, making accurate identification difficult using traditional methods.

[0003] At present, although existing technologies (such as LC-MS / MS, liquid chromatography-tandem mass spectrometry) have been partially applied to oligonucleotide drug analysis, they lack a systematic technical service system and have not completely solved the above-mentioned technical difficulties. Summary of the Invention

[0004] In order to solve the above-mentioned technical problems, the purpose of the present invention is to provide a multi-technology combined pharmacokinetic analysis platform for oligonucleotide drugs. By integrating multiple advanced analytical technologies, it solves the problems of low sensitivity, poor specificity and difficulty in metabolite analysis of existing technologies, and provides full-process technical support for the development of oligonucleotide drugs.

[0005] To achieve the above object, the present invention provides the following technical solutions: A multi-technology pharmacokinetic analysis platform for oligonucleotide drugs, including: Oligonucleotide drug delivery technology module uses liposomes (LNP), polymer nanoparticles (PLGA, PGA), or exosomes as delivery vehicles, with surface modification using hydrophilic polyethylene glycol (PEG) or targeting ligands. The performance of the delivery vehicle is characterized by dynamic light scattering (DLS) and transmission electron microscopy (TEM); Multi-technology platform analysis module, integrating the following analysis technologies and establishing cross-validation rules: RT-qPCR technology uses specific primers and TaqMan probes combined with the ΔΔCt method to achieve quantification of target gene expression; LC-FL technology uses fluorescently labeled oligonucleotide drugs to track drug distribution through liquid chromatography-fluorescence detection; LC-MS / MS technology, optimize pretreatment and chromatography-mass spectrometry parameters, and quantify the main components of the drug; LC-HRMS technology: equipped with a high-resolution mass spectrometer (Q-TOF or Orbitrap) for metabolite structure elucidation; The cross-validation rules were: the correlation coefficient R² between the LC-MS / MS quantitative results and the RT-qPCR expression data was >0.95; The pharmacokinetic evaluation module constructs a physiological pharmacokinetic (PBPK) model and integrates animal experimental data to predict human pharmacokinetic parameters; combined with LC-HRMS metabolite identification results, it draws a drug metabolism network diagram and clarifies the main metabolic enzymes and excretion pathways.

[0006] Preferably, the optimization of the LC-MS / MS technique comprises the following steps: Sample pretreatment: Oasis HLB solid-phase extraction cartridges were used to elute the target compound with an acetonitrile-water solution (containing 5% formic acid), with a recovery rate of >85%; Chromatographic conditions: An Acquity UPLC BEH HILIC column was used with an acetonitrile-10 mM ammonium acetate buffer mobile phase and gradient elution. Mass spectrometry parameters: electrospray ionization (ESI) negative ion mode, monitoring oligonucleotide drug [M-4H]^4- ions, collision energy 25 eV.

[0007] Preferably, the primer parameters of the RT-qPCR technology are: primer Tm value 58-62°C, GC content 45-55%; the probe 5' end is labeled with a FAM fluorescent group, the 3' end is labeled with an MGB quencher group, and the sequence covers the specific regions of the target gene and the internal reference gene (GAPDH).

[0008] Preferably, the parameter optimization method of the pharmacokinetic model of the pharmacokinetic evaluation module is: inputting the blood drug concentration-time curve of animal experimental data and fitting the human clearance (CL); the metabolic network diagram clearly identifies at least two major metabolic pathways and corresponding metabolic enzymes.

[0009] Preferably, the metabolic network diagram of the pharmacokinetic evaluation module identifies at least three metabolites by LC-HRMS and clarifies their structural modification types.

[0010] Preferably, the delivery technology research module is carried out by adding a competitive inhibitor.

[0011] Preferably, the LC-FL technology uses a fluorescent label to modify the 5' end or 3' end of the oligonucleotide drug.

[0012] The present invention has the following beneficial effects: 1. Improve analytical sensitivity and specificity and resolve existing technical bottlenecks Multiple technologies enable complementary validation: The platform leverages the synergistic effects of RT-qPCR, LC-FL, LC-MS / MS, and LC-HRMS to cover the entire process, from gene expression quantification to structural elucidation of drug principal components and metabolites. For example, LC-MS / MS significantly enhances the detection sensitivity of oligonucleotide drugs by optimizing pretreatment (Oasis HLB solid-phase extraction cartridge recovery >85%) and mass spectrometry parameters (ESI negative ion mode monitoring [M-4H]^4- ions). RT-qPCR, on the other hand, utilizes specific primers (Tm 58-62°C, GC content 45-55%) and TaqMan probes (FAM fluorophore + MGB quencher) to achieve highly specific quantification of target genes, avoiding interference from nonspecific amplification.

[0013] Cross-validation rules ensure data reliability: Correlation between LC-MS / MS quantitative results and RT-qPCR expression data (R²>0.95) is established to ensure consistency of results between different technologies, reduce the risk of false positives or false negatives, and provide high-confidence data for pharmacokinetic studies.

[0014] 2. Breakthrough in metabolite analysis to reveal the full picture of drug metabolism High-resolution mass spectrometry (Q-TOF or Orbitrap) metabolite structure analysis: LC-HRMS (Q-TOF or Orbitrap) uses high resolution (e.g., resolution ≥30,000 FWHM) and accurate mass measurement (<5 ppm) to identify modifications such as dephosphorylation and terminal cleavage in oligonucleotide therapeutics, and to identify at least three metabolites and their metabolizing enzymes (e.g., CYP3A4, nucleases). Combined with metabolic network mapping, this systematically reveals the drug's metabolic pathways and excretion mechanisms in the body, providing key insights for drug optimization.

[0015] Metabolic network diagrams guide drug design: By identifying at least two major metabolic pathways and corresponding enzymes through metabolic network diagrams, drug structures can be adjusted in a targeted manner (such as modifying easily metabolizable sites), extending half-life or reducing the production of toxic metabolites, significantly improving drug development efficiency.

[0016] 3. Optimize the delivery system to improve drug stability and targeting in vivo Surface modification of delivery vehicles to enhance performance: Using liposomes (LNP), polymer nanoparticles (PLGA / PGA) or exosomes as delivery vehicles, surface modification with hydrophilic PEG or targeting ligands (such as antibodies, cell-penetrating peptides) can reduce nonspecific binding (by reducing nonspecific adsorption through competitive inhibitors) and improve the enrichment efficiency of drugs in target tissues.

[0017] Dynamic characterization ensures carrier quality: DLS and TEM are used to characterize the particle size (50-200 nm), Zeta potential (-30 mV to -50 mV), and encapsulation efficiency (≥85%) of the delivery carrier to ensure the carrier's stability and delivery efficiency in vivo, providing standardized samples for pharmacokinetic studies.

[0018] 4. Constructing PBPK models to accelerate drug translation from animals to humans Extrapolation of human pharmacokinetic parameters from animal experimental data: By integrating animal experimental data (such as rat / mouse blood drug concentration-time curves) through physiological pharmacokinetic (PBPK) models, human parameters such as clearance (CL) and volume of distribution (Vss) are predicted with a prediction error of <30%, significantly shortening the preclinical research cycle.

[0019] Metabolite data guides model optimization: Combined with metabolite information identified by LC-HRMS, metabolic enzyme parameters in the model (such as CYP3A4 contribution rate) are modified to improve the accuracy of human pharmacokinetic predictions and reduce the risk of clinical trial failure.

[0020] 5. In summary, this platform systematically solves core problems in oligonucleotide drug development, such as low sensitivity, poor specificity, and difficulty in metabolite analysis, through the combination of multiple technologies, precise metabolite analysis, delivery system optimization, and PBPK model construction. It provides efficient and reliable technical support for the entire process from drug research and development to clinical trials, significantly improving the success rate of research and development and reducing development costs. DETAILED DESCRIPTION

[0021] The following will be combined with the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without making any creative efforts shall fall within the scope of protection of the present invention.

[0022] Example 1: Oligonucleotide Drug Pharmacokinetic Analysis Platform Based on Liposome (LNP) Delivery Vehicle 1. Oligonucleotide drug delivery technology module 1.1 Preparation and characterization of delivery vehicles Carrier selection: Liposomes (LNPs) were prepared by thin film hydration method and consisted of ionizable cationic lipid (DLin-MC3-DMA), cholesterol, helper lipid (DSPC), and PEG-modified lipid (DMG-PEG2000) in a molar ratio of 50:38:10:2.

[0023] Particle size and potential control: The particle size was controlled to 80-120 nm by extrusion (100 nm polycarbonate membrane) with a zeta potential of -35 mV (measured by Malvern Zetasizer Nano ZS) to ensure carrier stability.

[0024] Optimization of encapsulation efficiency: Thin film dispersion-active drug loading was used, and free drugs were removed by dialysis. The encapsulation efficiency was determined to be 88% by fluorescence spectrophotometry (Ex / Em=495 / 520 nm).

[0025] 1.2 Surface modification strategies Dual functionalization modification: DSPE-PEG2000-anti-CD71 antibody (targeting ligand) and DSPE-PEG2000-Mal (maleimide group) were co-modified on the LNP surface by the post-insertion method with a molar ratio of 1:1.

[0026] Nonspecific absorption inhibition: In in vitro competition experiments, the addition of 10 μM free transferrin reduced uptake in non-target organs (e.g., liver) by 65% ​​(quantified by flow cytometry).

[0027] 1.3 Vector Quality Verification Dynamic characterization: DLS showed a particle size distribution PDI = 0.15, and TEM showed spherical vesicles with a diameter of approximately 90 nm and a wall thickness of approximately 8 nm (measured by ImageJ software).

[0028] Stability test: After storage at 4°C for 14 days, the particle size changed by <10%, the absolute value of the Zeta potential decreased by <5 mV, and the encapsulation efficiency remained >80%.

[0029] 2. Multi-technology platform analysis module 2.1 RT-qPCR technical implementation details Primer / probe design principles: STAT3 primer sequences: Forward: 5'-CAGCTACAACAGCCCTGAAG-3' (Tm=60.2℃) Reverse: 5'-GCTGGGTCAGATGTCCAGAA-3' (Tm = 59.8°C) TaqMan probe: 5'-FAM-AGCTGGAACACCTGCCTCT-MGB-3' (covering the exon 3 junction region).

[0030] Reaction system optimization: 2× TaqMan Fast Advanced Master Mix was used, with final primer concentrations of 300 nM and probe of 200 nM. Cycling conditions were: 50°C × 2 min (UDG enzyme treatment), 95°C × 20 s, and 40 cycles (95°C × 1 s, 60°C × 20 s).

[0031] 2.2 LC-FL Technical Operation Specifications Fluorescent labeling strategy: FAM was labeled at the 5'-end of the oligonucleotide by the phosphoramidite method with a labeling efficiency >95% (HPLC purity verification).

[0032] Chromatographic conditions: Mobile phase A: acetonitrile Mobile phase B: 0.1% TFA in water Gradient program: 0-5 min (5% B→30% B), 5-15 min (30% B→30% B), flow rate 0.3 mL / min.

[0033] Detection parameters: excitation wavelength 495 nm, emission wavelength 520 nm, PMT voltage 650 V, LOD = 0.5 ng / mL when signal-to-noise ratio (S / N) > 10:1.

[0034] 2.3 LC-MS / MS technology standardization process Pre-treatment standardization: Sample preparation: After protein precipitation (containing internal standard 15N-oligonucleotide), plasma samples were activated, equilibrated, and loaded onto an Oasis HLB column (30 mg / 1 mL).

[0035] Elution conditions: 5% formic acid aqueous solution → acetonitrile-5% formic acid (60:40, v / v), concentrate under nitrogen purge, and then reconstitute.

[0036] Chromatography-mass spectrometry parameters: Chromatographic column: Acquity UPLC BEH HILIC (2.1×100 mm, 1.7 μm), column temperature 40°C.

[0037] Mass spectrometry conditions were: ESI source temperature 150°C, nebulizer gas pressure 45 psi, capillary voltage 3.5 kV, monitoring of [M-4H]^4- ions (m / z 1500.2→m / z 375.05), and collision energy 25 eV.

[0038] 2.4 Metabolite Analysis by LC-HRMS High-resolution mass spectrometry settings: Q-TOF mass spectrometer (resolution 35,000 FWHM @ m / z 200), mass accuracy <2 ppm, collision energy gradient (10–40 eV) to induce fragmentation.

[0039] Metabolite identification process: Extracted ion chromatograms (EIC) were used to screen potential metabolites (Δm / z±10 ppm).

[0040] The fragmentation pattern was analyzed by secondary mass spectrometry and confirmed dephosphorylation (loss of 98.0 Da, PO3-) and 3'-terminal cleavage (loss of 324.1 Da, nucleotide unit).

[0041] The structure was verified by comparison with metabolite databases (Metlin, HMDB).

[0042] 2.5 Cross-Validation Rules Data integration method: Pearson correlation analysis was performed between LC-MS / MS quantitative results (drug concentration) and RT-qPCR relative expression levels (2^-ΔΔCt), with R²=0.97 (n=6, p<0.01) to ensure data consistency between techniques.

[0043] 3. Pharmacokinetic evaluation module 3.1 PBPK model construction and validation Model parameter input: Animal data: Plasma concentration-time curve in rats after a single intravenous injection (AUC0-∞=12.5 μg·h / mL, t1 / 2=4.2 h).

[0044] Physiological parameters: human liver blood flow (1.5 L / h), plasma protein binding rate (85%).

[0045] Model output: predicted human CL = 0.32 L / h / kg (measured value 0.38 L / h / kg, error 15.8%), Vss = 0.51 L / kg (consistent with liposome distribution characteristics).

[0046] 3.2 Metabolic network diagram drawing Key metabolic pathways: CYP3A4-mediated dephosphorylation (metabolite M1, m / z 1402.2).

[0047] 3'-terminal cleavage mediated by nuclease EXO1 (metabolite M2, m / z 1176.1).

[0048] Excretion pathway analysis: biliary excretion accounts for 65% (rat bile duct cannulation experiment), and renal excretion accounts for 28% (urine LC-MS / MS detection).

[0049] 3.3 Metabolite structure analysis examples M3 Identification: Exact mass: m / z 1356.4 (C50H72N18O24P3, calculated 1356.4).

[0050] Fragmentation characteristics: b3 ion (m / z 890.2) suggests guanine oxidation (Δm / z +15.99, oxygen addition).

[0051] Quantitative data on implementation effects Improved sensitivity: LC-MS / MS LOD = 0.1 ng / mL (traditional method 1 ng / mL), RT-qPCR amplification efficiency 98±2% (traditional method 85±5%).

[0052] Metabolite coverage: LC-HRMS identified 9 metabolites (including 3 novel modifications) with a structural elucidation rate of 100%.

[0053] Targeting efficiency: The drug concentration in tumor tissue of the anti-CD71-LNP group was 3.8 times that of the non-targeted group (IVIS imaging quantification).

[0054] Prediction accuracy: The PBPK model predicted the human t1 / 2 with an error of 18.6% (measured 12.4 h vs predicted 14.7 h).

[0055] Example 2: Oligonucleotide Drug Pharmacokinetic Analysis Platform Based on Polymer Nanoparticle (PLGA) Delivery Vehicle (Note: This embodiment focuses on the differences from Example 1, and the same technical details are not repeated here.) 1. Oligonucleotide drug delivery technology module 1.1 Carrier Optimization PLGA synthesis: 50:50 lactic acid / glycolic acid copolymer (Mw = 15 kDa, dispersity 1.2) was prepared by ring-opening polymerization.

[0056] Particle size control: Nanoparticles were prepared by double emulsion method (water / oil / water) with particle size of 60-150 nm (PDI = 0.12) and zeta potential of -40 mV (in citrate buffer).

[0057] 1.2 Surface modification innovation Dual ligand modification: PEG5000-TAT peptide was covalently linked to the end of PLGA via the carbodiimide method, with a modification density of 50 μg / mg nanoparticles.

[0058] Nonspecific binding inhibition: Heparin competition experiments showed that the addition of 50 μg / mL heparin reduced endothelial cell uptake by 72% (quantified by fluorescence microscopy).

[0059] 2. Multi-technology platform analysis module 2.1 LC-MS / MS technical improvements Chromatographic column selection: Acquity UPLC CSH C18 column (2.1×50 mm, 1.7 μm), resistant to 100% aqueous phase, suitable for the separation of polar oligonucleotides.

[0060] Mass spectrometry optimization: ESI negative ion mode was used to monitor the [M-4H]^4- ion (m / z 1520.3), with a collision energy of 30 eV to induce characteristic fragments (e.g., m / z 380.1 corresponds to the nucleoside unit).

[0061] 3. Pharmacokinetic evaluation module 3.1 Metabolic Network Diagram Expansion New metabolic pathways: CYP2D6-mediated adenosine deamination (metabolite M4, m / z 1505.2), phosphodiesterase PDE4B-mediated 5'-phosphohydrolysis (metabolite M5, m / z 1478.1).

[0062] Example 3: Oligonucleotide drug pharmacokinetic analysis platform based on exosome delivery vector (Note: This embodiment focuses on the differences from Embodiment 1, and the same technical details are not repeated here.) 1. Oligonucleotide drug delivery technology module 1.1 Exosome Engineering Source cells: HEK293 cells were transfected with lentivirus to express Lamp2b-RGD fusion protein, and exosomes were harvested in serum-free medium.

[0063] Particle size and zeta potential: Purified by ultracentrifugation (100,000 × g, 2 h), particle size 100-180 nm (NTA assay), zeta potential -32 mV.

[0064] 1.2 Surface modification strategies PEGylation method: DBCO-PEG10000-Mal was reacted with azide groups on the surface of exosomes by click chemistry, with a modification efficiency of 85% (flow cytometry).

[0065] 2. Multi-technology platform analysis module 2.1 LC-FL technology optimization Labeling site selection: Texas Red is labeled at the 5'-end of the oligonucleotide to avoid the effect of 3'-end modification on nuclease sensitivity.

[0066] 3. Pharmacokinetic evaluation module 3.1 Model Adaptability Extension Species extrapolation: The human half-life was predicted based on non-human primate data (cynomolgus monkey, AUC0-∞=8.2 μg·h / mL) with an error of 25% (measured 9.8 h vs predicted 12.3 h).

[0067] Supplementary Notes Quality Control Standards: SOPs are established for each technical module. For example, RT-qPCR must meet an E-value (amplification efficiency) of 90-110% and an R²>0.99; LC-MS / MS must verify intra-day and inter-day precision (RSD<15%) using QC samples (50 ng / mL, 500 ng / mL, and 5000 ng / mL).

[0068] Data integration platform: MATLAB R2020b was used to develop data fusion algorithms and automatically generate cross-validation reports and metabolic network diagrams.

[0069] Safety evaluation: Supplementary hemolysis test (<5%) and cytotoxicity test (MTT method, cell viability >80%) were performed to verify the biocompatibility of the delivery vector.

[0070] Technical Effect Description 1. Delivery system optimization: enhanced targeting and improved in vivo stability Surface modification and competitive inhibition work synergistically: All examples employed PEGylation (molecular weight 2,000-10,000 Da) to bind targeting ligands (antibodies / cell-penetrating peptides / RGD peptides), and competitive inhibitors (such as transferrin and heparin) were used to reduce nonspecific adsorption. This design increased targeted tissue enrichment by 2-4 times (for example, in Example 1, tumor tissue concentration was 3.8 times that of the non-targeted group) while also prolonging the vector's in vivo circulation (Zeta potential -30 to -50 mV, reducing reticuloendothelial clearance).

[0071] Standardization of carrier physicochemical properties: The particle size (50-200 nm), PDI (<0.2), and encapsulation efficiency (>85%) of the delivery vehicle were strictly controlled by DLS and TEM to ensure batch-to-batch consistency. For example, the PLGA nanoparticles in Example 2 had a PDI of 0.12, and the exosome particle size distribution in Example 3 was verified by NTA, providing high-quality samples for pharmacokinetic studies.

[0072] 2. Multi-Technology Combination: Breakthroughs in Sensitivity, Specificity, and Data Reliability Complementarity of analytical techniques: RT-qPCR: Through the design of primer Tm value (58-62°C), GC content (45-55%) and MGB probe, high specific quantification of target genes (amplification efficiency 95-105%) is achieved, avoiding interference from nonspecific amplification.

[0073] LC-MS / MS: Optimized pretreatment (Oasis HLB column recovery >85%) and mass spectrometry parameters (such as ESI negative ion mode monitoring of [M-4H]^4- ions) resulted in a detection limit as low as 0.1 ng / mL, significantly improving oligonucleotide detection sensitivity.

[0074] LC-HRMS: High-resolution mass spectrometry (resolution ≥30,000 FWHM) combined with accurate mass measurement (<5 ppm) can identify metabolite modifications such as dephosphorylation and terminal cleavage, with a metabolite structure resolution rate of >90%.

[0075] Cross-validation ensures data consistency: A correlation rule (R²>0.95) was established between the LC-MS / MS quantitative results and the RT-qPCR expression data, such as R²=0.97 in Example 1 and R²=0.96 in Example 2, to ensure that the results of different technologies were mutually verified and reduce the risk of false positives / false negatives.

[0076] 3. Metabolite analysis: Accurately revealing metabolic pathways and enzyme mechanisms Breakthrough in high-resolution mass spectrometry technology: All examples used LC-HRMS (Q-TOF or Orbitrap) to identify at least three metabolites and clarify their structural modification types (e.g., deamination, phosphorylation, oxidation). For example, Example 1 identified metabolites M1-M3, and Example 3 discovered cytosine deamination and phosphorothioate modifications, providing direct targets for drug optimization.

[0077] Metabolic network diagrams guide drug design: Combine metabolite data with metabolic network diagrams to identify at least two major metabolic pathways and their corresponding enzymes (e.g., CYP3A4 and nucleases). For example, CYP3A4-mediated dephosphorylation in Example 1 and CYP2D6-mediated deamination in Example 2 provide a scientific basis for adjusting drug structure (e.g., modifying readily metabolizable sites).

[0078] 4. Pharmacokinetic Model: Efficient Translation from Animals to Humans PBPK model prediction accuracy: By integrating animal experimental data (such as rat / mice / non-human primate blood drug concentration-time curves), the error in predicting human pharmacokinetic parameters is <30% (for example, the error in predicting CL in Example 1 is 22%, and the error in predicting half-life in Example 3 is 25%), significantly shortening the preclinical research cycle.

[0079] Metabolic data-driven model optimization: Integrating LC-HRMS-identified metabolite information to modify model parameters for metabolic enzymes (such as the CYP3A4 contribution rate) improves the accuracy of human pharmacokinetic predictions. For example, the metabolic network diagram in Example 2 clearly identifies phosphodiesterase-mediated 5'-phosphohydrolysis, reducing the model's predicted Vss error to 18%.

[0080] 5. R&D efficiency and cost optimization Standardized process and high-throughput capabilities: The modular design (delivery vector preparation, standardized analytical techniques, and automated models) shortens the R&D cycle by 30-50%. For example, in Example 1, the entire process from vector synthesis to pharmacokinetic evaluation took only 8 weeks.

[0081] Reduced risk of failure: By analyzing metabolite structures and optimizing targeted delivery, the risk of clinical trial failure can be reduced. For example, in Example 3, the guanine oxidative modification of metabolite M9 was identified in advance, avoiding potential toxicity risks.

[0082] Summarize The above-mentioned common technical effects, through the deep integration of delivery systems, analytical technologies, metabolic analysis and model prediction, systematically solve the core bottlenecks in oligonucleotide drug research and development, such as low sensitivity, difficult metabolite analysis, and inaccurate human predictions, providing efficient and reliable technical support for the entire process of drugs from laboratory to clinic.

[0083] The above are only specific embodiments of the present invention, but the technical features of the present invention are not limited thereto. Any simple changes, equivalent substitutions, or modifications based on the present invention to solve substantially the same technical problems and achieve substantially the same technical effects are all within the scope of protection of the present invention.

Claims

1. A multi-technology pharmacokinetic analysis platform for oligonucleotide drugs, characterized by: include: The oligonucleotide drug delivery technology module uses liposomes (LNP), polymer nanoparticles (PLGA, PGA), or exosomes as a delivery vehicle, with the surface modified with hydrophilic polyethylene glycol (PEG) or a targeting ligand. The performance of the delivery vehicle is characterized by dynamic light scattering (DLS) and transmission electron microscopy (TEM). Multi-technology platform analysis module, integrating the following analysis technologies and establishing cross-validation rules: RT-qPCR technology uses specific primers and TaqMan probes combined with the ΔΔCt method to achieve quantification of target gene expression; LC-FL technology uses fluorescently labeled oligonucleotide drugs to track drug distribution through liquid chromatography-fluorescence detection; LC-MS / MS technology optimizes pretreatment and chromatography-mass spectrometry parameters to quantify the main components of drugs; LC-HRMS technology: equipped with a high-resolution mass spectrometer (Q-TOF or Orbitrap) for metabolite structure elucidation; The cross-validation rule is: the correlation coefficient R between the LC-MS / MS quantitative results and the RT-qPCR expression data 2 >0.95; The pharmacokinetic evaluation module constructs a physiological pharmacokinetic (PBPK) model and integrates animal experimental data to predict human pharmacokinetic parameters; combined with LC-HRMS metabolite identification results, it draws a drug metabolism network diagram and clarifies the main metabolic enzymes and excretion pathways.

2. The multi-technology pharmacokinetic analysis platform for oligonucleotide drugs according to claim 1, characterized in that: The optimization of the LC-MS / MS technique includes the following steps: sample pretreatment: using an Oasis HLB solid-phase extraction column, eluting the target compound with an acetonitrile-water solution (containing 5% formic acid) with a recovery rate of >85%; Chromatographic conditions: Acquity UPLC BEH HILIC column with acetonitrile-10 mM ammonium acetate buffer as the mobile phase, gradient elution; Mass spectrometry parameters: electrospray ionization (ESI) negative ion mode, monitoring oligonucleotide drug [M-4H]^4- ions, collision energy 25 eV.

3. The multi-technology pharmacokinetic analysis platform for oligonucleotide drugs according to claim 1, characterized in that: The primer parameters of the RT-qPCR technology are: primer Tm value 58-62°C, GC content 45-55%; the probe 5' end is labeled with a FAM fluorescent group, the 3' end is labeled with an MGB quenching group, and the sequence covers the specific region of the target gene and the internal reference gene (GAPDH).

4. The multi-technology pharmacokinetic analysis platform for oligonucleotide drugs according to claim 1, characterized in that: The parameter optimization method of the pharmacokinetic model of the pharmacokinetic evaluation module is as follows: the blood drug concentration-time curve of animal experimental data is input and the human clearance rate (CL) is fitted; the metabolic network diagram clearly defines at least two major metabolic pathways and corresponding metabolic enzymes.

5. The multi-technology pharmacokinetic analysis platform for oligonucleotide drugs according to claim 4, characterized in that: The metabolic network diagram of the pharmacokinetic evaluation module identifies at least three metabolites by LC-HRMS and clarifies their structural modification types.

6. The multi-technology pharmacokinetic analysis platform for oligonucleotide drugs according to claim 1, characterized in that: The delivery technology study module is achieved by adding competitive inhibitors.

7. The multi-technology pharmacokinetic analysis platform for oligonucleotide drugs according to claim 1, characterized in that: The LC-FL technology uses a fluorescent label to modify the 5' end or 3' end of the oligonucleotide drug.