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All Journal HAYATI Journal of Biosciences JURNAL PETERNAKAN Science and Technology Indonesia Jurnal Fitofarmaka Indonesia Pharmaceutical Sciences and Research (PSR) Eduvest - Journal of Universal Studies Jurnal Farmasi Indonesia

Sutriyo

Fakultas Farmasi Universitas Indonesia

Author-ID : 623440

Aerospace Engineering Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Earth & Planetary Sciences Environmental Science Health Professions Materials Science & Nanotechnology Medicine & Pharmacology Neuroscience Physics Social Sciences

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Untargeted LC-QTOF-MS/MS Based Metabolomic Profile Approach of Bacterial Ferment Lysates and Skin Commensal Bacterial Cocktail Ferment Lysates Ahmad Baikuni; Fathan Luthfi Hawari; Sutriyo; Delly Ramadon; Amarila Malik
HAYATI Journal of Biosciences Vol. 30 No. 3 (2023): May 2023
Publisher : Bogor Agricultural University, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.4308/hjb.30.3.576-587

Microbial therapy has been increasingly developed in the medical and health fields and has triggered advances in the process of formulating skincare products. The skin microbiota becomes the target in the development of active ingredients to produce an optimal effect in the balance of its composition which leads to its usefulness in maintaining skin health and providing protection. Postbiotic bacteria can maintain homeostasis of the skin microbiome so that it has the potential to be used as an active ingredient in Active Pharmaceutical Ingredient (API) in skincare products and have broad benefits due to its various active substances. The aim of this study was to examine the metabolites profile contained in the bacterial fermented lysate fraction, which is also served as a marker in identifying the metabolite variations of the lysate fractions and their API dosage forms. Ferment lysate API preparations were prepared in the form of freeze dried and spray dried. The metabolite profile analysis was carried out using the untargeted LC-QTOF-MS/MS metabolomic approach and multivariate analysis. Result revealed 30 differential features of the putative metabolites, and by performing metabolites annotationfor their bioactivities through intensive literature research, such as antimicrobial, antioxidant, and anti-inflammatory, we elucidated these compounds are discovered in dry form of lysates.

Isolation of Cellulase from Selected Fungal Strains and Its Use for Manufacture Microcrystal Cellulose from Kapuk Cortex (Ceiba Pentandra (L.) Gaertn) Mi'rajunnisa; Herman Suryadi; Sutriyo; Yulianita Pratiwi Indah Lestari
Science and Technology Indonesia Vol. 8 No. 2 (2023): April
Publisher : Research Center of Inorganic Materials and Coordination Complexes, FMIPA Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26554/sti.2023.8.2.227-234

This study aims to obtain cellulase enzymes from selected molds for microcrystalline cellulose preparation from ????-cellulose of kapok cortex. Alpha-cellulose was obtained by biodelignification, and the purified cellulase was obtained from the selected mold. The Microcrystalline cellulose obtained from enzymatic hydrolysis was then identified FTIR and DSC, followed by characterization of microcrystalline cellulose, Particle Size and Distribution Analysis (PSA), and Scanning Electron Microscope-Energy Dispersive X-ray (SEM-EDX), Loss on drying, pH, bulk density, tapped density, and flow rate. Biodelignification produced 14.88% ????-cellulose, Penicillium sp. the selected mold had the highest cellulase activity, with a cellulolytic index of 4.83. FTIR identification was similar to Avicel PH 101 with a melting point of 244.580°C. Loss on drying was 3.74%, pH was 7.0, particle size ranged from 13.06 to 196.79 ????m, bulk density and tapped density were 0.11 g/cm3 and 0.23 g/cm3, respectively flow rate character is quite good. SEM-EDX was showed that the morphological shape of the microcrystalline cellulose of the kapok cortex is elongated. Microcrystalline cellulose has shown a quite similar in character and can be furthered.

The In-vivo Safety and Efficacy Test of Antiaging Serum Containing Gold Nanoparticle Synthesized Using Sida rhombifolia Extract Waluyo, Dyah Ayuwati; Sutriyo, Sutriyo Sutriyo; Vardhani, Afifah K.; Wardana, Mutia Sari
Jurnal Fitofarmaka Indonesia Vol 11, No 3 (2024): JURNAL FITOFARMAKA INDONESIA (ENGLISH EDITION)
Publisher : Faculty of Pharmacy, Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/jffi.v11i3.1212

Advance glycation end products (AGEs) are the basic root cause of endogenous aging. AGEs causing fragmentations and crosslinked collagen which damaging the skin integrity and mechanical properties resulting in reduced skin elasticity. Gold nanoparticles (AuNP) has been synthetized using Sida rhombifolia (Sidaguri) extract. This study aimed to determine the efficacy of antiaging serum containing AuNP synthetized using Sidaguri extract. AuNP was produced by reducing HAuCl4 solution using Sidaguri extract. 10% of AuNP colloid was formulated into the serum. 19 woman applied patch containing serum and base placebo to perform irritation test followed by provocative test if there is any reddish reaction found. 16 women showed no signs of irritation and 3 women showed a reddish reaction, the provocative test showed no signs of irritation. Then efficacy test performed to 18 women by applying 1 drop of the serum at one side of the forearm and base placebo serum at the other side, after passing patch test. The antiaging serum had the ability to increase skin collagen (64.72 ± 27.11%) and skin elasticity (64.11 ± 11.67%) after 8 weeks of use, twice a day. There was a significant increase in skin collagen and elasticity index (P-value < 0.0001).

Formulasi Sabun Cair Perak Nanopartikel dengan Penstabil Polyvinil Alcohol : Sabun Cair Perak Nanopartikel Sutriyo; Hanandi, Sharon; Putri, Kurnia Sari Setio; Poetri, Okti Nadia; Annisa, Syifa; Rahmasari, Ratika
JFIOnline | Print ISSN 1412-1107 | e-ISSN 2355-696X Vol 13 No 1 (2021): Jurnal Farmasi Indonesia
Publisher : Pengurus Pusat Ikatan Apoteker Indonesia

According to Global Burden of Disease reported on 2019, about 1.53 million deaths caused by infectious diseases such as pneumonia and diarrhea. Triclosan is one of the active ingredient commonly used in antibacterial soap as one way to prevent the spread of infectious disease.. However, bacteria resistance against triclosan has been reported. Silver nanoparticles (AgNP) is an alternative antibacterial that potential to be used in liquid hand wash. However AgNp tend to aggregate during storage, thus stabilizer is needed This study aims to synthesize AgNP, formulate the liquid hand wash contain AgNP with polyvinil alcohol as stabilizer, and evaluate its effectiveness against Escherichia coli, Staphylococcus aureus, and Salmonella thypi. AgNP was prepared using the chemical reduction method between silver nitrate and sodium borohydride, followed by its characterization using UV-Vis spectrophotometer, TEM, PSA, and AAS. The physical characteristic of AgNp-liquid hand wash were also evaluated. Further, the antibacterial activity of AgNP-handwash was evaluated by phenol coefficient method. The peak of UV absorption spectrum of colloidal was found at 404.2 nm indicated the presence of AgNP. Ag content in AgNP colloidal was 38.405 mg/Kg ± 0,008. The spherical shape of AgNP was observed. The AgNP size was 65.1 nm with polydispersity index value of 0.543, and zeta potential value was -22.25 mV. The obtained AgNP-hand wash met the Indonesian standard criteria and was stable for 28 days. The best phenol coefficient value was obtained at formulation with addition of 30% AgNP (0.1 for S. typhi, 0.4 for E. coli, and 0.01 for S. aureus).

Formulasi Nasal Spray Anti-Influenza yang Mengandung Nanopartikel Perak : Nasal Spray Anti-Influenza Nanopartikel Perak Sutriyo; Wilbert Wylie; Kurnia Sari Setio Putri; Okti Nadia Poetri; Rahmasari, Ratika
JFIOnline | Print ISSN 1412-1107 | e-ISSN 2355-696X Vol 13 No 2 (2021): Jurnal Farmasi Indonesia
Publisher : Pengurus Pusat Ikatan Apoteker Indonesia

Influenza A virus is one of the most common causes of respiratory disease in the world. Even though, vaccines and anti-influenza virus are become the first line for therapy, but the mutation ability of influenza virus is able to cause several outbreaks in the world. Silver nanoparticles (AgNP) have been proven to exhibit antiviral activity; however, the use of AgNP in pharmaceutical products is still limited. In this study, we aimed to formulate nasal spray containing AgNP, to evaluate its physicochemical properties, and its antiviral activity toward H5N1 influenza A virus. AgNP were synthesized using chemical reduction method with polyvinyl alcohol as stabilizer, and further prepared into nasal spray product. Physicochemical properties and anti-hemagglutination activity of nasal spray were further evaluated. The nasal spray contained different size of AgNP (less and more than 50 nm) showed physical stability after 28 days storage. However, Anti-influenza evaluation of nasal spray contained AgNP less than 50 nm exhibited better anti-hemagglutination activity against influenza A virus.

Evaluation And Selection Of Optimal Deep Learning Architecture For Predicting The Endpoint In High Shear Wet Granulation For Antacid Tablet Production Irvan Maulana; Arry Yanuar; Sutriyo Sutriyo; Alhadi Bustamam
Eduvest - Journal of Universal Studies Vol. 4 No. 6 (2024): Journal Eduvest - Journal of Universal Studies
Publisher : Green Publisher Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59188/eduvest.v4i6.1274

Objective: The purpose of this research was to evaluate and select the best architecture among native convolutional neural network (CNN), MobileNetV2, ResNet50V2, and EfficientNetB0 for predicting the endpoint of the high shear wet granulation process, with accuracy as the main evaluation metric. Methods: The dataset was captured from an industrial camera using static image analysis and was manually labeled as “NOT READY” and “READY” according to the traditional endpoint method based on the mixer’s ampere point in the granulator. The dataset contained a total of 180 images, which were split between training and validation sets. Native CNN and TensorFlow Keras application programming interface (API) were utilized with MobileNetV2, EfficientNetB0, and ResNet50V2 as base feature encoders. Hyperparameters, such as final Fully Connected (FC) layer width, dropout rate, and learning rate, were optimized for binary classification using Keras hyper tuning. Results: The best was the native CNN, it was also the fastest among the three other models, taking only 20-30 ms per step for inference during runtime, though it requires 9000 ms time for training, the longest time among the models. It achieved an accuracy of 98%, and a validation accuracy of 97%. Conclusion: The system was able to determine when a wet granulation process has reached its endpoint based on live images from a camera after being trained on previously labeled data. The native CNN was the best model, offering the fastest runtime performance and the highest accuracy.

Utilization of Near-Infrared Spectroscopy Combined with PLS-2 Regression Learner to Predict Metformin HCL Tablet Dissolution Profile Mohamad Rahmatullah Zakaria; Sutriyo Sutriyo; Hayun Hayun; Taufiq Indra Rukmana
Eduvest - Journal of Universal Studies Vol. 5 No. 1 (2025): Journal Eduvest - Journal of Universal Studies
Publisher : Green Publisher Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59188/eduvest.v5i1.1566

One of the assurances of pharmaceutical tablet's quality, effectivity, and safety is the dissolution test, which is commonly known by pharmaceutical manufacturers. Conventionally, this test is performed by simulating the release rate of a drug using a Dissolution Tester, which mimics the human gastrointestinal condition. As stated by the current compendial for tablet dosage form, the dissolution rate is mandatory, with no exception for Metformin HCl tablets. This laboratory method is often time-consuming, unsafe for organic reagent exposure, and produces waste. This problem requires rapid, simple, and nondestructive technologies, hence having powerful analytical performance. One of the technologies that is widely used is Near Infrared (NIR) spectroscopy. This study utilized the NIR spectrum as a predictor to generate a mathematical model using Partial Least Square Regression (PLS-2) to build a dissolution rate model for the Metformin HCl tablet, which uses the Farmakope Indonesia IV <1231> (FI-IV) dissolution method as the compendial reference method. The PLS-2 model was built, which shows the low difference between SEC and SECV in each sampling point and a good correlation in the coefficient of determination (R2) of each point's time of dissolution within 0.900 to 0.953. The challenge test was performed to prove the predictability of the PLS-2 model with NIR against the actual reference FI-IV method using differential and similarity Factors (f2 & f1), enabling real-time release testing (RTRT).

Co-Authors . Hayun . Khairunnisya . Rosmaladewi . Sundarsih Abdul Mun'ím Abdul Mun'Ãm Adilla Novitasari Adilla Novitasari, Adilla Ahmad Baikuni Amarila Malik Annisa, Syifa Arry Yanuar Bustamam, Alhadi Dian Hayati Dian Hayati Dyah Ayuwati Waluyo Fathan Luthfi Hawari Febrian Hevike Filosane Febrian Hevike Filosane, Febrian Hevike Hanandi, Sharon Hasan Rachmat Hasan Rachmat, Hasan Herman Suryadi Indah, Rosari Irvan Maulana Iskandarsyah Joshita Djajadisastra Joshita Djajadisastra Joshita Djajadisastra Joshita Djajadisastra Joshita Djajadisastra, Joshita Khairunnisya, Khairunnisya Kurnia Sari Setio Putri, Kurnia Sari Setio Mega Suryani Mega Suryani, Mega Mi'rajunnisa Mita Rosalina Mita Rosalina, Mita Mohamad Rahmatullah Zakaria Mun’im, Abdul Mutia Sari Wardana Okti Nadia Poetri Rahmasari, Ratika RAMADON, DELLY Rarah Ratih Adjie Maheswari Rosari Indah Rosmala Dewi Rosmala Dewi Siti Nur Aeni Siti Nur Aeni, Siti Nur Sundarsih, Sundarsih Taufiq Indra Rukmana Vardhani, Afifah K. Wieda Nurwidada Haritsa Zain Wilbert Wylie Yulianita Pratiwi Indah Lestari Zuraida Syafara Dzuhro Zuraida Syafara Dzuhro Zuraida Syafara Dzuhro Zuraida Syafara Dzuhro, Zuraida Syafara

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