Tool For Drug Development Research Articles

Advancement of Network Pharmacology in Multi-targeted Therapeutic Evaluation of Medicinal Plants

In recent years, network pharmacology has emerged as a powerful approach for understanding the complex interactions between various bioactive components of medicinal plants and their targets within biological systems [1,2]. This approach plays a pivotal role in evaluating the multi-targeted therapeutic potential of medicinal plants, making it a promising tool for drug discovery and development. The integration of traditional knowledge with modern analytical techniques and computational methods has enabled the comprehensive exploration of the pharmacological properties of medicinal plants [3-6]. Medicinal plants have been an essential part of traditional medicine systems worldwide for centuries. These plants contain a wide array of bioactive compounds, such as alkaloids, flavonoids, terpenoids, and polyphenols, which exert therapeutic effects through interactions with specific molecular targets [7,8]. However, elucidating the intricate relationships between these compounds and their targets has proven challenging [2].

Latest developments in engineered skeletal muscle tissues for drug discovery and development

ABSTRACT Introduction With the advances in skeletal muscle tissue engineering, new platforms have arisen with important applications in biology studies, disease modeling, and drug testing. Current developments highlight the quest for engineering skeletal muscle tissues with higher complexity . These new human skeletal muscle tissue models will be powerful tools for drug discovery and development and disease modeling. Areas covered The authors review the latest advances in in vitro models of engineered skeletal muscle tissues used for testing drugs with a focus on the use of four main cell culture techniques: Cell cultures in well plates, in microfluidics, in organoids, and in bioprinted constructs. Additional information is provided on the satellite cell niche. Expert opinion In recent years, more sophisticated in vitro models of skeletal muscle tissues have been fabricated. Important developments have been made in stem cell research and in the engineering of human skeletal muscle tissue. Some platforms have already started to be used for drug testing, notably those based on the parameters of hypertrophy/atrophy and the contractibility of myotubes. More developments are expected through the use of multicellular types and multi-materials as matrices . The validation and use of these models in drug testing should now increase.

Organ Chips and Visualization of Biological Systems.

Organ-on-a-chip (OOC) is an emerging frontier cross-cutting science and technology developed in the past 10 years. It was first proposed by the Wyss Institute for Biologically Inspired Engineering of Harvard Medical School. It consists of a transparent flexible polymer the size of a computer memory stick, with hollow microfluidic channels lined with living human cells. Researchers used bionics methods to simulate the microenvironment of human cells on microfluidic chips, so as to realize the basic physiological functions of corresponding tissues and organs in vitro. Transparent chip materials can perform real-time visualization and high-resolution analysis of various human life processes in a way that is impossible in animal models, so as to better reproduce the microenvironment of human tissue and simulate biological systems in vitro to observe drug metabolism and other life processes. It provides innovative research systems and system solutions for in vitro bionics of biological systems. It also has gradually become a new tool for disease mechanism research and new drug development. In this chapter, we will take the current research mature single-organ-on-a-chip and multi-organ human-on-a-chip as examples; give an overview of the research background and underlying technologies in this field, especially the application of in vitro bionic models in visualized medicine; and look forward to the foreseeable future development prospects after the integration of organ-on-chip and organoid technology.

3D collagen microchamber arrays for combined chemotherapy effect evaluation on cancer cell numbers and migration.

Breast cancer metastasis involves complex mechanisms, particularly when patients are undergoing chemotherapy. In tissues, tumor cells encounter cell-cell interactions, cell-microenvironment interactions, complex nutrient, and drug gradients. Currently, two-dimensional cell culture systems and animal models are challenging to observe and analyze cell responses to microenvironments with various physical and bio-chemical conditions, and microfluidic technology has been systematically developed to address this dilemma. In this study, we have constructed a combined chemotherapy evaluation chip (CCEC) based on microfluidic technology. The chip possesses 192 diamond-shaped microchambers containing MDA-MB-231-RFP cells, and each microchamber is composed of collagen to mimic breast cancer and its surrounding microenvironment. In addition, by adding medium containing different drugs to the medium channels of CCEC, composite drug (paclitaxel+gemcitabine+7rh and paclitaxel+fluorouracil+PP2) concentration gradients, and single drug (paclitaxel, gemcitabine, 7rh, fluorouracil, PP2) concentration gradients have been established in the five collagen regions, respectively, so that each localized microchamber in the regions has a unique drug microenvironment. In this way, we evaluated the composite and single chemotherapy efficacy on the same chip by statistically analyzing their effects on the numbers and migration of the cell. The quantitative results in CCECs reveal that the inhibition effects on the numbers and migration of MDA-MB-231-RFP cell under the composite drug gradients are more optimal than those of the single drugs. Besides, the cancer cell inhibition effect between the groups composed of two drugs has also been compared, that is the paclitaxel+gemcitabine, paclitaxel+fluorouracil, and paclitaxel+PP2 have better cell numbers and migration inhibition effects than paclitaxel+7rh. The results indicate that the bio-mimetic and high-throughput combined chemotherapy evaluation platform can serve as a more efficient and accurate tool for preclinical drug development and screening.

PLANEJAMENTO DE FÁRMACOS CONTRA COVID-19: UMA EXPERIÊNCIA DE ENSINO REMOTO DE QUÍMICA FARMACÊUTICA

DRUG DESIGN AGAINST COVID-19: A REMOTE TEACHING EXPERIENCE IN PHARMACEUTICAL CHEMISTRY. Infront of with the difficulties faced in making a new drug available to the population, it is essential to seek ways to simplify the process. In silico methodologies are alternatives to benchtop experiments, being frequently used due to their speed and low cost. The present study aimed to formulate a theoretical-practical activity in the Pharmaceutical Chemistry course, where students applied their knowledge of structural modeling and molecular docking to propose bioactive compounds against molecular targets of the SARS-CoV-2 virus. The class was divided, and each group presented a drug candidate, the precursors being natural molecules. In total, seven derivatives were designed and tested against different macromolecules, and then an in silico prediction of their physicochemical characteristics was performed. The docking results were positive for all derivatives, in terms of binding energy, mainly GEND with –9.0 kcal mol-1. In addition, the prototypes exhibited good interactions with the amino acids of the respective targets, mainly KAED, QUED and GEND, in addition to presenting adequate physicochemical properties for meeting the Lipinski restrictions. Therefore, this study presented at least three potential inhibitors of SARS-CoV-2, showing the importance of using computational tools in drug design and development, as well as in teaching practice.

Closed-chest occlusion of the left anterior descending artery in swine infarction model

Pigs have played a significant role in biological and medical research for many years. In the case of non-rodent models, pigs are the primary choices as experimental animals in the cardiovascular studies. Accumulating data indicate that the closed-chest coronary balloon-occlusion technique is one of the most successful method for creating ischemic heart failure (HF). However, consistent and thoroughly characterized large animal models of HF are a critical translational tool for drug development and toxicology. The knowledge of the different catheterization protocols is crucial to ensure a suitable animal model which can serve as a human-related preclinical validation process. Therefore it is essential to follow an optimized and standardized experimental protocol on a homogenous animal population, which help to obtain reliable and useful data for the translational large animal research programs.

Polycystic Kidney Disease Drug Development: A Conference Report

Autosomal dominant polycystic kidney disease (ADPKD) is part of a spectrum of inherited diseases that also includes autosomal recessive polycystic kidney disease, autosomal dominant polycystic liver disease, and an expanding group of recessively inherited disorders collectively termed hepatorenal fibrocystic disorders. ADPKD is the most common monogenic disorder frequently leading to chronic kidney failure with an estimated prevalence of 12 million people worldwide. Currently, only one drug (tolvaptan) has been approved by regulatory agencies as disease-modifying therapy for ADPKD, but, given its mechanism of action and side effect profile, the need for an improved therapy for ADPKD remains a priority. Although significant regulatory progress has been made, with qualification of total kidney volume as a prognostic enrichment biomarker and its later designation as a reasonably likely surrogate endpoint for progression of ADPKD within clinical trials, further work is needed to accelerate drug development efforts for all forms of PKD. In May 2021, the PKD Outcomes Consortium at the Critical Path Institute and the PKD Foundation organized a PKD Regulatory Summit to spur conversations among patients, industry, academic, and regulatory stakeholders regarding future development of tools and drugs for ADPKD and autosomal recessive polycystic kidney disease. This Special Report reviews the key points discussed during the summit and provides future direction related to PKD drug development tools.

MiDruglikeness: Subdivisional Drug-Likeness Prediction Models Using Active Ensemble Learning Strategies.

The drug development pipeline involves several stages including in vitro assays, in vivo assays, and clinical trials. For candidate selection, it is important to consider that a compound will successfully pass through these stages. Using graph neural networks, we developed three subdivisional models to individually predict the capacity of a compound to enter in vivo testing, clinical trials, and market approval stages. Furthermore, we proposed a strategy combing both active learning and ensemble learning to improve the quality of the models. The models achieved satisfactory performance in the internal test datasets and four self-collected external test datasets. We also employed the models as a general index to make an evaluation on a widely known benchmark dataset DEKOIS 2.0, and surprisingly found a powerful ability on virtual screening tasks. Our model system (termed as miDruglikeness) provides a comprehensive drug-likeness prediction tool for drug discovery and development.

Mode of action of vinca alkaloids against cancer using Insilco analysis technique

Plants have been known for their medicinal properties across the world for a long time. In the field of medicine, medicinal plants have played a critical role. Catharanthus roseus is one such plant with enormous medical significance and potential. C.roesus, often known as Madagascar periwinkle, is a major drug-producing plant. More than 200 alkaloids are found in all parts of the plant, including the leaf, root, shoot, and stem, and are used to treat a variety of diseases. Vinca alkaloids are also effective cancer fighters. To see the mode of action of vinca alkaloids against cancer, 3D structure of Tubulin alpha-beta dimer was obtained from the database, The vinca alkaloids were obtained from Zinc database. In recent years, protein-ligand docking has become a powerful tool for drug development. The final PDB file of Tubulin alpha-beta dimer (PDB Id: 1TUB) and alkaloids were directly fed into an online docking server, SwissDock (http://www.swissdock.ch/docking). In this research we will find out that how Vinca alkaloids are commonly used in combination chemotherapy regimens for medicinal treatments. The vinca alkaloids have cytotoxic properties that can halt cell division and cause cell death.

Metabolomics and Network Pharmacology in the Exploration of the Multi-Targeted Therapeutic Approach of Traditional Medicinal Plants

Metabolomic is generally characterized as a comprehensive and the most copious analytical technique for the identification of targeted and untargeted metabolite diversity in a biological system. Recently, it has exponentially been used for phytochemical analysis and variability among plant metabolites, followed by chemometric analysis. Network pharmacology analysis is a computational technique used for the determination of multi-mechanistic and therapeutic evaluation of chemicals via interaction with the genomes involved in targeted or untargeted diseases. In considering the facts, the present review aims to explore the role of metabolomics and network pharmacology in the scientific validation of therapeutic claims as well as to evaluate the multi-targeted therapeutic approach of traditional Indian medicinal plants. The data was collected from different electronic scientific databases such as Google Scholar, Science Direct, ACS publication, PubMed, Springer, etc., using different keywords such as metabolomics, techniques used in metabolomics, chemometric analysis, a bioinformatic tool for drug discovery and development, network pharmacology, methodology and its role in biological evaluation of chemicals, etc. The screened articles were gathered and evaluated by different experts for their exclusion and inclusion in the final draft of the manuscript. The review findings suggest that metabolomics is one of the recent most precious and effective techniques for metabolite identification in the plant matrix. Various chemometric techniques are copiously used for metabolites discrimination analysis hence validating the unique characteristic of herbal medicines and their derived products concerning their authenticity. Network pharmacology remains the only option for the unique and effective analysis of hundreds of chemicals or metabolites via genomic interaction and thus validating the multi-mechanistic and therapeutic approach to explore the pharmacological aspects of herbal medicines for the management of the disease.

Two-enzyme cascade catalyzed trideuteromethylative modification of natural products

Site-selective incorporation of the trideuterated “magic methyl” group may provide profound pharmacological benefits, which has been considered as an important tool for drug optimization and development in medicinal chemistry. S-adenosyl-L-methionine (SAM) usually acts as the methyl donor under the catalysis of SAM-dependent methyltransferases (MTs), which transfer a methyl group from SAM to substrates, and are widely reported for methylation in natural product biosynthesis. However, it is difficult to introduce other high-value functional groups to substrates in this way since SAM analogs are not easy to obtain in biological methods. Herein we report that trideuterated SAM can be obtained from S-adenosylhomocysterine (SAH) and trideuterated methyl iodide (CD3I) under the participation of halide methyltransferase (HMT). Subsequent one-pot cascades with different MTs achieved the regioselective trideuteromethylation of three natural products, which indicated that trideuterated SAM can be accepted as a co-substrate by C-, N-, O-specific MTs for enzyme-catalyzed trideuteromethylation of natural products.

Generation of Functional Immortalized Human Corneal Stromal Stem Cells.

In addition to their therapeutic potential in regenerative medicine, human corneal stromal stem cells (CSSCs) could serve as a powerful tool for drug discovery and development. Variations from different donors, their isolation method, and their limited life span in culture hinder the utility of primary human CSSCs. To address these limitations, this study aims to establish and characterize immortalized CSSC lines (imCSSC) generated from primary human CSSCs. Primary CSSCs (pCSSC), isolated from human adult corneoscleral tissue, were transduced with ectopic expression of hTERT, c-MYC, or the large T antigen of the Simian virus 40 (SV40T) to generate imCSSC. Cellular morphology, proliferation capacity, and expression of CSSCs specific surface markers were investigated in all cell lines, including TNFAIP6 gene expression levels in vitro, a known biomarker of in vivo anti-inflammatory efficacy. SV40T-overexpressing imCSSC successfully extended the lifespan of pCSSC while retaining a similar morphology, proliferative capacity, multilineage differentiation potential, and anti-inflammatory properties. The current study serves as a proof-of-concept that immortalization of CSSCs could enable a large-scale source of CSSC for use in regenerative medicine.

ACP-ADA: A Boosting Method with Data Augmentation for Improved Prediction of Anticancer Peptides.

Cancer is the second-leading cause of death worldwide, and therapeutic peptides that target and destroy cancer cells have received a great deal of interest in recent years. Traditional wet experiments are expensive and inefficient for identifying novel anticancer peptides; therefore, the development of an effective computational approach is essential to recognize ACP candidates before experimental methods are used. In this study, we proposed an Ada-boosting algorithm with the base learner random forest called ACP-ADA, which integrates binary profile feature, amino acid index, and amino acid composition with a 210-dimensional feature space vector to represent the peptides. Training samples in the feature space were augmented to increase the sample size and further improve the performance of the model in the case of insufficient samples. Furthermore, we used five-fold cross-validation to find model parameters, and the cross-validation results showed that ACP-ADA outperforms existing methods for this feature combination with data augmentation in terms of performance metrics. Specifically, ACP-ADA recorded an average accuracy of 86.4% and a Mathew’s correlation coefficient of 74.01% for dataset ACP740 and 90.83% and 81.65% for dataset ACP240; consequently, it can be a very useful tool in drug development and biomedical research.

Functionalization of Radiolabeled Antibodies to Enhance Peripheral Clearance for High Contrast Brain Imaging.

Small molecule imaging agents such as [11C]PiB, which bind to the core of insoluble amyloid-β (Aβ) fibrils, are useful tools in Alzheimer's disease (AD) research, diagnostics, and drug development. However, the [11C]PiB PET signal saturates early in the disease progression and does not detect soluble or diffuse Aβ pathology which are believed to play important roles in the disease progression. Antibodies, modified into a bispecific format to enter the brain via receptor-mediated transcytosis, could be a suitable alternative because of their diversity and high specificity for their target. However, the circulation time of these antibodies is long, resulting in an extended exposure to radiation and low imaging contrast. Here, we explore two alternative strategies to enhance imaging contrast by increasing clearance of the antibody ligand from blood. The bispecific Aβ targeting antibody RmAb158-scFv8D3 and the monospecific RmAb158 were radiolabeled and functionalized with either α-d-mannopyranosylphenyl isothiocyanate (mannose) or with trans-cyclooctene (TCO). While mannose can directly mediate antibody clearance via the liver, TCO-modified antibody clearance was induced by injection of a tetrazine-functionalized, liver-targeting clearing agent (CA). In vivo experiments in wild type and AD transgenic mice demonstrated the ability of both strategies to drastically shorten the circulation time of RmAb158, while they had limited effect on the bispecific variant RmAb158-8D3. Furthermore, single photon emission computed tomography imaging with TCO-[125I]I-RmAb158 in AD mice showed higher contrast 1 day after injection of the tetrazine-functionalized CA. In conclusion, strategies to enhance the clearance of antibody-based imaging ligands could allow imaging at earlier time points and thereby open the possibility to combine antibodies with short-lived radionuclides such as fluorine-18.

In Vitro and In Vivo Characterization of 89Zirconium-Labeled Lintuzumab Molecule.

Objective: Positron emission tomography (PET) imaging is a powerful non-invasive method to determine the in vivo behavior of biomolecules. Determining biodistribution and pharmacokinetic (PK) properties of targeted therapeutics can enable a better understanding of in vivo drug mechanisms such as tumor uptake, off target accumulation and clearance. Zirconium-89 (89Zr) is a readily available tetravalent PET-enabling radiometal that has been used to evaluate the biodistribution and PK of monoclonal antibodies. In the current study, we performed in vitro and in vivo characterization of 89Zr-lintuzumab, a radiolabeled anti-CD33 antibody, as a model to evaluate the in vivo binding properties in preclinical models of AML. Methods: Lintuzumab was conjugated to p-SCN-Bn-deferoxamine (DFO) and labeled with 89Zr using a 5:1 µCi:µg specific activity at 37 °C for 1h. The biological activity of 89Zr-lintuzumab was evaluated in a panel of CD33 positive cells using flow cytometry. Fox Chase SCID mice were injected with 2 × 106 OCI-AML3 cells into the right flank. After 12 days, a cohort of mice (n = 4) were injected with 89Zr-lintuzumab via tail vein. PET/CT scans of mice were acquired on days 1, 2, 3 and 7 post 89Zr-lintuzumab injection. To demonstrate 89Zr-lintuzumab specific binding to CD33 expressing tumors in vivo, a blocking study was performed. This cohort of mice (n = 4) was injected with native lintuzumab and 24 h later 89Zr-lintuzumab was administered. This group was imaged 3 and 7 days after injection of 89Zr-lintuzumab. A full ex vivo biodistribution study on both cohorts was performed on day 7. The results from the PET image and ex vivo biodistribution studies were compared. Results: Lintuzumab was successfully radiolabeled with 89Zr resulting in a 99% radiochemical yield. The 89Zr-lintuzumab radioconjugate specifically binds CD33 positive cells in a similar manner to native lintuzumab as observed by flow cytometry. PET imaging revealed high accumulation of 89Zr-lintuzumab in OCI-AML3 tumors within 24h post-injection of the radioconjugate. The 89Zr-lintuzumab high tumor uptake remains for up to 7 days. Tumor analysis of the PET data using volume of interest (VOI) showed significant blocking of 89Zr-lintuzumab in the group pre-treated with native lintuzumab (pre-blocked group), thus indicating specific targeting of CD33 on OCI-AML3 cells in vivo. The tumor uptake findings from the PET imaging study are in agreement with those from the ex vivo biodistribution results. Conclusions: PET imaging of 89Zr-lintuzumab shows high specific uptake in CD33 positive human OCI-AML3 tumors. The results from the image study agree with the observations from the ex vivo biodistribution study. Our findings collectively suggest that PET imaging using 89Zr-lintuzumab could be a powerful drug development tool to evaluate binding properties of anti-CD33 monoclonal antibodies in preclinical cancer models.

Preclinical models for development of immune-oncology therapies.

Immunotherapy has demonstrated great success in clinical treatment, especially for cancer care. Here we review preclinical models, including cell lines, three dimensional (3D) cultures, and mouse models to support the need for tools enabling the development of novel immune-oncology (I-O) therapies. While in vitro studies have the advantage of being relatively simpler, faster, and higher throughput than in vivo models, they must be designed carefully to recapitulate the biological conditions that influence drug efficacy. The growing prevalence of 3D in vitro and ex vivo models has enabled screening and mechanistic studies in more complex, tissue-like environments containing multiple interacting cell types. On the other hand, syngeneic mouse models have been instrumental in the historical development of immunotherapies and remain an important tool in drug development, despite lacking fidelity to certain aspects of human physiology and pathology. Xenograft and humanized mouse models address some of these challenges, yet present limitations of their own. Successful development and translation of new I-O therapies will likely require thoughtful combination of several of these preclinical models, and we aim to help research and development scientists utilize the appropriate tools and technologies to facilitate rapid transition from preclinical evaluation to clinical trials.

Attenuation of Potassium Bromate-induced Infertility by African Locust Bean (Parkia biglobosa) Seed

Background: Parkia biglobosa seed has been reported to enhance sperm quality. Thus, this study sought to assess its ability in attenuating KBrO3-induced sperm abnormalities.
 Methodology: P. biglobosa was extracted with soxhlet extractor with 95% ethanol as the solvent. Twenty-four adult male Wistar rats were acclimatized under laboratory conditions and were randomly grouped into A, B, C and D. Group A was given distilled water orally. Animals in groups B, C and D were administered 100 mg/kg body weight of potassium bromate, but groups C and D were also treated with 100 and 200 mg/kg body weight of P. biglobosa respectively. Both potassium bromate and P. biglobosa were freshly prepared on daily basis and administered to rats by oral gavage. After 28 days of treatment, the animals were sacrificed under mild diethyl ether anaesthetization 24 hours after cessation of the last treatment. The cauda epididymis were separated from both testes and tinged with 2 mL of normal saline then teased. The suspension was mixed through a metallic net to avoid any other tissue contamination. This suspension was used for the determination of the sperm parameters.
 Results: Exposure of animals to 100 mg/kg body weight of KBrO3 significantly reduced sperm count, sperm motility, sperm viability and seminal pH but elevated sperm morphology when compared with animals in the control group at p<0.05. These perturbations were attenuated by 100 and 200 mg/kg body weight of P. biglobosa seed extract in a dose-dependent manner.
 Conclusion: The result of this study showed that potassium bromate induced abnormalities in sperm cells of treated animals, and seed extract of P. biglobosa attenuated these abnormalities in a dose-dependent manner. This pharmacological study is a useful tool for further drug development from the natural plant products.

Machine learning and artificial intelligence in physiologically based pharmacokinetic modeling.

Physiologically based pharmacokinetic (PBPK) models are useful tools in drug development and risk assessment of environmental chemicals. PBPK model development requires the collection of species-specific physiological, and chemical-specific absorption, distribution, metabolism, and excretion (ADME) parameters, which can be a time-consuming and expensive process. This raises a need to create computational models capable of predicting input parameter values for PBPK models, especially for new compounds. In this review, we summarize an emerging paradigm for integrating PBPK modeling with machine learning (ML) or artificial intelligence (AI)-based computational methods. This paradigm includes 3 steps (1) obtain time-concentration PK data and/or ADME parameters from publicly available databases, (2) develop ML/AI-based approaches to predict ADME parameters, and (3) incorporate the ML/AI models into PBPK models to predict PK summary statistics (eg, area under the curve and maximum plasma concentration). We also discuss a neural network architecture "neural ordinary differential equation (Neural-ODE)" that is capable of providing better predictive capabilities than other ML methods when used to directly predict time-series PK profiles. In order to support applications of ML/AI methods for PBPK model development, several challenges should be addressed (1) as more data become available, it is important to expand the training set by including the structural diversity of compounds to improve the prediction accuracy of ML/AI models; (2) due to the black box nature of many ML models, lack of sufficient interpretability is a limitation; (3) Neural-ODE has great potential to be used to generate time-series PK profiles for new compounds with limited ADME information, but its application remains to be explored. Despite existing challenges, ML/AI approaches will continue to facilitate the efficient development of robust PBPK models for a large number of chemicals.

Patient-specific in vitro drug release testing coupled with in silico PBPK modeling to forecast the in vivo performance of oral extended-release levodopa formulations in Parkinson’s disease patients

Biorelevant in vitro release models are valuable analytical tools for oral drug development but often tailored to gastrointestinal conditions in ‘average’ healthy adults. However, predicting in vivo performance in individual patients whose gastrointestinal conditions do not match those of healthy adults would be of great value for optimizing oral drug therapy for such patients. This study focused on establishing patient-specific in vitro and in silico models to predict the in vivo performance of levodopa extended-release products in Parkinson’s disease patients. Current knowledge on gastrointestinal conditions in these patients was incorporated into model development. Relevant in vivo pharmacokinetic data and patient-specific in vitro release data from a novel in vitro test setup were integrated into patient-specific physiologically-based pharmacokinetic models. AUC, cmax and tmax of the computed plasma profiles were calculated using PK-Sim®. For the products studied, levodopa plasma concentration–time profiles modeled using this novel approach compared far better with published average plasma profiles in Parkinson’s disease patients than those derived from in vitro release data obtained from the ‘average’ healthy adult setup. Although further work is needed, results of this study highlight the importance of addressing patient-specific gastrointestinal conditions when aiming to predict drug release in such specific patient groups.

Novel Bioactive Compounds from Marine Sources as a Tool for Drug Development

The marine environment is a relatively unexplored source of functional ingredients that can be used in food processing, storage, and fortification in a variety of ways. Marine microorganisms are a possible source of novel bioactive chemicals with potential human utility. Some of these microbes can live in the harsh marine environments, resulting in complex compounds with unique biological properties that can be used in several industrial and biotechnological applications. So far, several marine microorganisms (fungi, myxomycetes, bacteria, and microalgae) have been isolated that produce antioxidant, antibacterial, apoptotic, antitumoral, and antiviral chemicals. Furthermore, it emphasizes the enormous potential for marine microbes to produce very important bioactive chemicals. They are used for new drug developments extensively across the world. Marine pharmacology offers the scope for research on these drugs of marine origin. Few institutes in India offer such opportunities which can help us in the quest for new drugs. This is an extensive review of the drugs developed and the potential new drug candidates from marine origin along with the opportunities for research on marine derived products. It also gives the information about the institutes in India which offer marine pharmacology related courses. Keywords: Anticancer, Bryostatin, Cytarabine, Keyhole limpet hemocyanin, Mariculture, Sponge, Ziconotide