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Investigational New Drugs

Investigational New Drugs (INDs) are experimental medications that are being studied for safety and efficacy prior to regulatory approval.
These drugs are not yet commercially available, but are undergoing clinical trials to determine their potential benefits and risks.
The research and development of INDs is a critical step in bringing new pharmaceutical treatments to patients.
PubCompare.ai's AI-driven platform helps researchers optimize their IND study protocols by locating the best literature, pre-prints, and patents to ensure reproducibility and accuracy.
Explore PubCompare.ai today to streamline your IND resaerch needs.

Most cited protocols related to «Investigational New Drugs»

1
Resting-State fMRI Preprocessing Pipeline
Cited 108 times

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Publication 2013
Brain Cerebrospinal Fluid ECHO protocol fMRI Homo sapiens Investigational New Drugs Magnetic Resonance Imaging Pharmaceutical Preparations TRIO protein, human White Matter
2
Comprehensive Molecular Catalog Compilation
Cited 93 times
We loaded catalogs from over 320 commercial vendors and 130 annotated catalogs. Some sources such as HMDB and DrugBank were loaded as several distinct catalogs in ZINC allowing us to leverage the curation of metabolite origin such as plant metabolites in HMDB or drug status such as investigational drugs in DrugBank. All catalogs in ZINC are categorized by their biogenic and bioactivity status, if any.95 Only descriptions that characterized the entire catalog contents were applied. For instance, the “Approved” subset of DrugBank was categorized as “World Drugs” since it contains over 100 drugs approved in other countries but not by FDA, and the “Endogenous” subset of HMDB was categorized as having a biogenic type of “endogenous human metabolite”. Molecules inherit biogenic and bioactive properties from the catalogs they are found in. These values are computed and stored, and are accessible in the interface as molecular features. There are four biogenic catalog levels: 1) Endogenous human metabolites, i.e. compounds that are synthesized in man. Interestingly, this may include compounds produced by our bacterial flora; 2) Metabolites of any species, i.e. small molecules that are involved in metabolism, development and reproduction, but not metabolites of xenobiotics; 3) Biogenic compounds, often called natural products; 4) Unknown biogenic status. Likewise, ZINC supports seven levels of bioactivity annotation as follows. 1) FDA approved; 2) World drugs; 3) Investigational, compounds reported to be used in clinical trials; 4) In Man, which including nutraceuticals, for instance; 5) In vivo, which includes DrugBank experimental compounds that have been in animals; 6) In cells, which includes compounds reported active in cell based assays; 7) In vitro, compounds active or assumed active at 10 μM or better in a direct binding assay. All other compounds are marked as having unknown biological activity. The categories are ordered to be progressively inclusive within each series, thus all FDA approved drugs are also world drugs and all compounds active in cells are also active in vitro. We annotate as building blocks those catalogs of compounds available in preparative quantities, typically 250 mg or more. Commercial vendors are categorized by the speed and cost of compound acquisition, allowing the best purchasability of every compound to be computed based on its current catalog membership. Catalog categorizations are refined continually by purchasing experience in our lab and reports from colleagues, as follows:95 1) In stock, delivery in under two weeks, 95% typical acquisition success rate; 2) Procurement agent, in stock, delivery in 2 weeks, 95% typical acquisition success rate; 3) Make-on-demand, delivery typically within 8 to 10 weeks, 70% typical acquisition success rate; 4) Boutique, where the cost may be high, but still likely cheaper than making it yourself, 70% typical acquisition success rate.
Sterling T, & Irwin J.J. (2015). ZINC 15 – Ligand Discovery for Everyone. Journal of Chemical Information and Modeling, 55(11), 2324-2337.
Publication 2015
Anabolism Animals Bacteria Biological Assay Biopharmaceuticals Cells Inclusion Bodies Investigational New Drugs Metabolism Natural Products Nutraceuticals Obstetric Delivery Pharmaceutical Preparations Plants Reproduction Xenobiotics Zinc
3
Standardized Drug Activity Evaluation
Cited 85 times
Drug activity levels expressed as 50% growth inhibitory levels (GI50s) are determined by the Developmental Therapeutics Program2 at 48 hours using the sulphorhodamine B assay (22 (link)). Repeat experiments must pass quality control criteria, similar to those for gene transcript levels. Experiments with range less than 1.2 log10 or with information on less than 35 cell lines are dropped. This serves to eliminate non-responsive and out of proper range data. The number of experiments that pass these criteria is determined, and 25% of that number calculated (keeping a minimum of 2 and a maximum of 122). Pearson’s correlations are determined for all remaining possible experiment/experiment combinations. Experiments whose average correlations are less than 0.334 (p<0.05 for the 35 cell line minimum in the absence of multiple comparisons correction) and were not correlated to individual probes at ≥ 0.334 are dropped. For the remaining experiments with average correlations less than 0.60 (p<0.00014 for the 35 cell line minimum), the lowest is dropped, and the correlations recalculated for all remaining possible experiment/experiment combinations. Experiments are dropped in this fashion until either all are ≥ to 0.60, or the 25% (of experiments that passed the 1.2 log2 range criteria) level is reached. This ensures significant pattern match across experiments. Drugs with only one experiment, but pass that the ≤1.2 log10 range test are included as output as they are potentially informative, but must be considered less reliable. For the purpose of this manuscript, compounds that have not yet undergone clinical trials will sometimes be referred to as drugs, as well as those that have.
Reinhold W.C., Sunshine M., Liu H., Varma S., Kohn K.W., Morris J., Doroshow J, & Pommier Y. (2012). CellMiner: a web-based suite of genomic and pharmacologic tools to explore transcript and drug patterns in the NCI-60 cell line set. Cancer Research, 72(14), 3499-3511.
Publication 2012
Biological Assay Cell Lines Genes Investigational New Drugs lissamine rhodamine B Pharmaceutical Preparations Psychological Inhibition Therapeutics
4
Retrospective Mutational Data Cohort Analysis
Cited 54 times
Retrospective mutational data were obtained from three publicly available sources: 1) The Cancer Genome Atlas (TCGA), 2) International Cancer Genome Consortium (ICGC), and 3) independent published sequencing projects(10 (link)). The subset of this cohort that was prospectively sequenced consists of 10,945 samples from 10,336 unique advanced cancer patients and whose tumors were profiled as part of their active care between January 2014 and July 2016 at Memorial Sloan Kettering Cancer Center (MSKCC). The consent of these patients, acquisition of specimens, sequencing, analysis, and reporting are described in an accompanying manuscript(8 (link)). All such patients provided written and informed consent for sequencing and review of patient medical records for detailed demographic, pathologic, and treatment information (NCT01775072). This study was approved by the Memorial Sloan Kettering Cancer Center Institutional review board and the studies were conducted in accordance with the Declaration of Helsinki, International Ethical Guidelines for Biomedical Research Involving Human Subjects (CIOMS), Belmont Report, or U.S. Common Rule. Briefly, matched tumor and normal specimens were sequenced (to 500–1000-fold sequence coverage) with a validated capture-based next-generation sequencing assay called MSK-IMPACT that is New York state-approved for clinical use. This assay captures the coding exons and select introns of oncogenes, tumor suppressor genes, all genes targeted by either approved therapies or those investigational drugs being studied in clinical trials at our Center, and significantly mutated genes reported by large-scale cancer sequencing efforts (Supplementary Table 2). These sequencing data are analyzed as previously described(1 (link)) to detect somatic mutations, small insertions and deletions (indels), DNA copy number alterations (CNAs) and select translocations using DNA from both frozen and formalin fixed-paraffin embedded tissue. An IRB protocol facilitates this prospective genomic characterization (IRB #12–245, ClinicalTrials.gov NCT01775072) and enables the return of results to patients. All genomic data generated as part of routine standard-of-care therapy is deposited, along with relevant clinical data, in a HIPAA-compliant manner, in the cBioPortal for Cancer Genomics(28 (link), 29 (link)). All somatic nonsynonymous mutations reported were manually reviewed in primary sequencing data as described in ref. (8 (link)) and combined with synonymous mutations in the same samples and utilized in this analysis. All mutations in any one of 469 genes that overlap among the retrospective and prospective subsets of the final cohort were uniformly re-annotated using vcf2maf ver. 1.6.10 (https://github.com/mskcc/vcf2maf). Variants identified by the Exome Aggregation Consortium (ExAC)(30 (link)) as having a minor allele frequency greater than 0.0004 in any subpopulation were excluded as presumed germline unless they were annotated by ClinVar(31 (link)) as either pathogenic, a risk factor, or protective.
Chang M.T., Bhattarai T.S., Schram A.M., Bielski C.M., Donoghue M.T., Jonsson P., Chakravarty D., Phillips S., Kandoth C., Penson A., Gorelick A., Shamu T., Patel S., Harris C., Gao J., Sumer S.O., Kundra R., Razavi P., Li B.T., Reales D.N., Socci N.D., Jayakumaran G., Zehir A., Benayed R., Arcila M.E., Chandarlapaty S., Ladanyi M., Schultz N., Baselga J., Berger M.F., Rosen N., Solit D.B., Hyman D.M, & Taylor B.S. (2017). Accelerating discovery of functional mutant alleles in cancer. Cancer discovery, 8(2), 174-183.
Publication 2017
Biological Assay Copy Number Polymorphism Diploid Cell Exome Exons Formalin Freezing Gene Deletion Genes Genome Germ Line INDEL Mutation Insertion Mutation Introns Investigational New Drugs Malignant Neoplasms Mutation Neoplasms Oncogenes Paraffin pathogenesis Patients Population Group Silent Mutation Therapeutics Tissues Translocation, Chromosomal Tumor Suppressor Genes
5
Comprehensive Drug-Target Interaction Dataset
Cited 54 times
Dataset for drugs and targets with known pharmacological interactions were extracted from DrugBank database (http://drugbank.ca/, accessed on June 1st 2011), which so far contains 6707 drug entries including 1436 FDA-approved small molecule drugs, 134 FDA-approved biotech (protein/peptide) drugs, 83 nutraceuticals and 5086 experimental drugs. Additionally, 4228 non-redundant protein (i.e. drug target/enzyme/transporter/carrier) sequences are also potentially linked to these entries. To confirm the quality of this data set, we have carefully compared this database with other databases such as STITCH, SuperTarget and KEGG database, as well as the literature [22] (link), [23] (link). In the process of building dataset, some drugs and targets (such as nitric oxide and ribosomal protein Thx) were omitted since their chemical descriptors cannot be calculated (details are provided in Supporting Information S1). As a result, a dataset including 6511 drugs and 3987 targets was applied in this work as the benchmark dataset (detailed information of these drugs and targets was given in Supporting Information S2 and S3).
Yu H., Chen J., Xu X., Li Y., Zhao H., Fang Y., Li X., Zhou W., Wang W, & Wang Y. (2012). A Systematic Prediction of Multiple Drug-Target Interactions from Chemical, Genomic, and Pharmacological Data. PLoS ONE, 7(5), e37608.
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Publication 2012
Drug Delivery Systems Enzymes Investigational New Drugs Membrane Transport Proteins Nutraceuticals Oxide, Nitric Peptides Pharmaceutical Preparations Proteins Ribosomal Proteins Synapsin I

Most recents protocols related to «Investigational New Drugs»

1
Cryptosporidium parvum Infection Model
Not available on PMC !

Example 51

The NOD SCID gamma mouse model of chronic, asymptomatic C. parvum infection was used to test in vivo compound efficacy. NOD SCID gamma mice were infected with ˜1×105 C. parvum oocysts by oral gavage 5-7 days after weaning. The infected animals begin shedding oocysts in the feces 1 week after infection, which is measured by quantitative PCR (qPCR). Based on experience with the positive control compound paromomycin, four mice are required per experimental group to achieve 80% power to detect an 80% percent reduction in parasite shedding after four days of drug compound. In additional to the experimental drug regimen groups, additional negative (gavage with DMSO/methylcellulose carrier) and positive (paromomycin 2000 mg/kg once daily) control groups are included in each experiment. Mice are infected 5-7 days after weaning (day −6), infection is confirmed 1 week later (day 0), and experimental compounds are dosed by oral gavage on days 1-4. The dosing frequency was as indicated. Treatment efficacy was assessed by measurement of fecal oocyst shedding by qPCR on day 5.

US11866441B2. Compounds and methods for the treatment of parasitic diseases (2024-01-09). THE BROAD INSTITUTE, INC. [US], PRESIDENT AND FELLOWS OF HARVARD COLLEGE [US]. Inventors: Eamon Comer [US], Nobutaka Kato [US], Marshall Morningstar [US], Bruno Melillo [US].
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Patent 2024
Animals Asymptomatic Infections Biological Assay Chronic Infection Drug Compounding Feces Gamma Rays Infection Investigational New Drugs Methylcellulose Mice, Inbred NOD Mus Oocysts Parasites Paromomycin SCID Mice Sulfoxide, Dimethyl Treatment Protocols Tube Feeding
2
Preparation of Flux Agent with Recovered Volatiles
Not available on PMC !

Example 3

In some experiments, high fructose corn syrup or another carbohydrate syrup was used without further processing as flux agent. In other experiments, a portion of the flux agent was prepared as follows:

A 200 mL plastic container was weighed and labeled. Approximately 150 g of fructose or a carbohydrate syrup was added to the container. Recovered volatiles from a coal conversion process described in U.S. Pat. No. 8,226,816 and US Published Patent Application 2015/0083570 were obtained by collection from vacuum distillation step. These recovered volatiles included a mixture of hydrocarbons with boiling points ranging from about 80° C. to about 300° C. About 7.5 g of recovered volatiles were added to the fructose or carbohydrate syrup in the plastic container.

The plastic container was then sealed and shaken vigorously by hand for 60 seconds to mix the components of the flux agent. No change was observed after an additional 60 seconds of shaking and the mixture was then considered homogeneous.

US11858818B2. Processes and compositions for carbon foam materials (2024-01-02). West Virginia University [US]. Inventors: Alfred H. Stiller [US].
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Patent 2024
Carbohydrates Coal Distillation Fructose High Fructose Corn Syrup Hydrocarbons Investigational New Drugs Neoplasm Metastasis Vacuum
3
Comparing Sacubitril/Valsartan and Valsartan in Pre-HFpEF
The Personalized Prospective Comparison of ARNI [angiotensin receptor/neprilysin inhibitor] with ARB [angiotensin-receptor blocker] in Patients With Natriuretic Peptide Elevation (PARABLE) randomized, double-blind, double-dummy, active comparator trial was conducted from April 2015 to June 2021 at a single outpatient cardiology center in Dublin, Ireland. The trial was designed to investigate the hypothesis that sacubitril/valsartan vs valsartan would reduce left atrial volume index over 18 months using volumetric cardiac magnetic resonance imaging in patients with pre-HFpEF. Ethical approval was obtained by the St Vincent’s University Hospital Ethics Committee and competent authority approval was obtained from the Health Protection Regulatory Authority in Ireland (EudraCT: 2015-002928-53; ClinicalTrials.gov identifier: NCT04687111). The protocol is available in Supplement 1. Further details on trial oversight, supply of investigational medicinal products, and contractual arrangements with the funder are provided in eMethods 1 in Supplement 2.
Ledwidge M., Dodd J.D., Ryan F., Sweeney C., McDonald K., Fox R., Shorten E., Zhou S., Watson C., Gallagher J., McVeigh N., Murphy D.J, & McDonald K. (2023). Effect of Sacubitril/Valsartan vs Valsartan on Left Atrial Volume in Patients With Pre–Heart Failure With Preserved Ejection Fraction: The PARABLE Randomized Clinical Trial. JAMA Cardiology, 8(4), 366-375.
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Publication 2023
Angiotensin Receptor Angiotensin Receptor Antagonists Atrium, Left Cardiovascular System Dietary Supplements Ethics Committees, Clinical Heart Investigational New Drugs Natriuretic Peptides Neprilysin Outpatients Patients sacubitril-valsartan Valsartan Visually Impaired Persons
4
Calcium-Magnesium-BHB Supplementation Trial
The investigational medicinal product (IMP) used in this clinical trial was 9 gr of D-BHB (from 18 gr racemic BHB) in powdered calcium (Ca2 +)–magnesium (Mg2 +)–salt form (Ca–Mg–BHB) divided into three servings per day. The mineral load determined the maximal IMP dose. The placebo group received sachets containing Mannitol.
Gross E.C., Putananickal N., Orsini A.L., Schoenen J., Fischer D, & Soto-Mota A. (2023). Defining metabolic migraine with a distinct subgroup of patients with suboptimal inflammatory and metabolic markers. Scientific Reports, 13, 3787.
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Publication 2023
Calcium, Dietary Investigational New Drugs Magnesium Mannitol Minerals Placebos Sodium Chloride
5
Automated Resonance Frequency Monitoring
The magnitude of change in resonance frequency of an element is indicated by the average difference in frequency (MHz) and SD (shown in figures as the error bar). From the start of culture to the end of measurement, the entire region where the bacterial suspension was present on the element and for which no change of − 10 MHz or less was observed before or after injection of the drug solution was used as the measurement area. Of the 1488 elements on the sensor array, 745–1260 elements (average: 1039; SD: 150) were automatically selected by the computer program for use in analysis. In accordance with these criteria, sensor elements that lost bacteria from the near-field after the injection of antibacterial drug or liquid medium were removed by an automated program. The growth ability was indicated by the mean difference in resonance frequency (MHz) starting from 0 h and the SD. DST was performed at two concentrations for some drugs (Supplementary Table 1). There were three control experiments, and one experiment for each drug. Because the temperature was controlled within ± 0.1 °C, the effect of each drug on BCG was determined from the time course of the difference (MHz) of each sensor element without correcting for changes in temperature. A histogram analysis was performed at 16 h after drug administration by using elemental measurements from each sensor (Fig. 3). The data analysis and graphs were prepared by using GraphPad Prism™ (version 9.2.0, GraphPad Software, Inc., San Diego, CA).
Kikuchi S., Yamashige Y., Hosoki R., Harata M, & Ogawa Y. (2023). Near-field sensor array with 65-GHz CMOS oscillators can rapidly and comprehensively evaluate drug susceptibility of Mycobacterium. Scientific Reports, 13, 3825.
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Publication 2023
Aftercare Anti-Bacterial Agents Bacteria Body Temperature Changes Indium Investigational New Drugs Pharmaceutical Preparations Pharmaceutical Solutions prisma Vibration

Top products related to «Investigational New Drugs»

1
Dimethyl sulfoxide (dmso) by Merck Group
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DMSO is a versatile organic solvent commonly used in laboratory settings. It has a high boiling point, low viscosity, and the ability to dissolve a wide range of polar and non-polar compounds. DMSO's core function is as a solvent, allowing for the effective dissolution and handling of various chemical substances during research and experimentation.
2
Fetal bovine serum (fbs) by Thermo Fisher Scientific
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Fetal Bovine Serum (FBS) is a cell culture supplement derived from the blood of bovine fetuses. FBS provides a source of proteins, growth factors, and other components that support the growth and maintenance of various cell types in in vitro cell culture applications.
3
Microplate reader by Agilent Technologies
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The Microplate reader is a versatile laboratory instrument used to measure and analyze the optical properties of samples in microplates. It is designed to quantify absorbance, fluorescence, or luminescence signals from various assays and applications.
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Sas version 9 by SAS Institute
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SAS version 9.4 is a statistical software package. It provides tools for data management, analysis, and reporting. The software is designed to help users extract insights from data and make informed decisions.
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Sas 9 by SAS Institute
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SAS 9.4 is an integrated software suite for advanced analytics, data management, and business intelligence. It provides a comprehensive platform for data analysis, modeling, and reporting. SAS 9.4 offers a wide range of capabilities, including data manipulation, statistical analysis, predictive modeling, and visual data exploration.
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Microinjection pump by Harvard Apparatus
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The Microinjection Pump is a precision instrument designed for accurately delivering small volumes of liquids or gases. It is commonly used in research applications that require controlled and repeatable micro-volume injections, such as cell microinjection, embryo manipulation, and other specialized laboratory procedures.
7
L glutamine by Thermo Fisher Scientific
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L-glutamine is an amino acid that is commonly used as a dietary supplement and in cell culture media. It serves as a source of nitrogen and supports cellular growth and metabolism.
8
Penicillin streptomycin by Thermo Fisher Scientific
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Penicillin/streptomycin is a commonly used antibiotic solution for cell culture applications. It contains a combination of penicillin and streptomycin, which are broad-spectrum antibiotics that inhibit the growth of both Gram-positive and Gram-negative bacteria.
9
Hydrocortisone by Merck Group
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Hydrocortisone is a laboratory-grade reagent used in various research and analytical applications. It is a synthetic corticosteroid compound with anti-inflammatory and immunosuppressant properties. Hydrocortisone is commonly utilized as a standard or reference material in analytical procedures, such as assays and chromatographic techniques, to quantify and identify related compounds.
10
Dulbecco modified eagle medium (dmem) by Thermo Fisher Scientific
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DMEM (Dulbecco's Modified Eagle's Medium) is a cell culture medium formulated to support the growth and maintenance of a variety of cell types, including mammalian cells. It provides essential nutrients, amino acids, vitamins, and other components necessary for cell proliferation and survival in an in vitro environment.

More about "Investigational New Drugs"

Investigational New Drugs (INDs) are experimental pharmaceutical compounds that are undergoing rigorous testing and evaluation before they can be approved for commercial use.
These novel drug candidates are not yet available on the market, but are being studied intensively to determine their safety, efficacy, and potential benefits for patients.
The research and development of INDs is a critical phase in the journey of bringing new medical treatments to those in need.
This process involves conducting clinical trials, which utilize specialized equipment and reagents like DMSO, FBS, Microplate readers, and L-glutamine to assess the drug's performance and impact.
Advanced data analysis tools, such as SAS version 9.4, are often employed to meticulously evaluate the results of these IND studies, ensuring reproducibility and accuracy.
Microinjection pumps may also be used to precisely administer the experimental drugs to study participants.
Throughout the IND research pipeline, maintaining strict quality control and sterile conditions is paramount.
This often requires the use of Penicillin/streptomycin and Hydrocortisone to prevent contamination and support cell growth in the DMEM culture medium.
Ultimately, the successful development of INDs is a crucial step in the quest to bring innovative, life-changing pharmaceutical treatments to those in need.
By leveraging cutting-edge technologies and robust research protocols, PubCompare.ai's AI-driven platform can help optimize the IND research process and accelerate the path to regulatory approval and commercial availability.