Anti Diabetics – Diabetics Symptoms Treatment Drug Dosage

Anti Diabetics Symptoms Epidemiology Treatment Drug Dosage

Diabetes mellitus, often simply referred to as diabetes—is a condition in which a person has high blood sugar, either because the body does not produce enough insulin, or because cells do not respond to the insulin that is produced. Diabetes mellitus is characterized by chronic hyperglycemia glycosuria, hyperlipemia, negative nitrogen balance and sometimes ketonemia with disturbances of carbohydrate, fat, and protein metabolism resulting from defects in insulin secretion, insulin action, or both.

This high blood sugar produces the classical symptoms of polyuria (frequent urination), polydipsia (increased thirst) and polyphagia (increased hunger).

There are three main types of diabetes:

Type 1 diabetes: results from the body’s failure to produce insulin, and presently requires the person to inject insulin.
Type 2 diabetes: results from insulin resistance, a condition in which cells fail to use insulin properly, sometimes combined with an absolute insulin deficiency.
Gestational diabetes: is when pregnant women, who have never had diabetes before, have a high blood glucose level during pregnancy.

Diagnosis

Diagnosis of Diabetics Symptoms Epidemiology Treatment Drug Dosage.png

EPIDIMEOLOGY:

There is an increase in the prevalence of type 1diabetes also, but main cause of diabetic epidemic is type2 diabetes mellitus, which accounts for more than 90 percent of all diabetes cases. According to World Health Organization (WHO) reports, India had 32 million diabetic people in the year 2001. The International Diabetes Federation (IDF) estimates the total number of diabetic subjects to be around 40.9 million in India and this is further set to rise to 69.9 million by the year 2025. The majority of cases of diabetes fall into two broad etiopathogenetic categories now called type 1 and T2 DM. The etiologic classification of diabetes mellitus currently recommended by WHO and the ADA in 1997.

ORAL HYPOGYCEMIC DRUGS

 Biguanide Metformin

 Sulfonylureas Glimepiride,gliclazide,glipizide,glyburide,glibenclamide

 Meglitinides Repaglinide,nateglinide

 Gliptins (DPP-4 inhibitors) Sitagliptin,vildagliptin,saxagliptin,alogliptin,linagliptin

 Thiazolidinediones (PPAR-γ agonists) Pioglitazone,rosiglitazone

Anti Diabetics Symptoms Epidemiology Treatment Drug Dosage

 α-Glucosidase inhibitors Acarbose,miglitol,voglibose

 Dopamine D2-receptor agonists Bromocriptine

SUBCUTANEOUS INJECTION

 Insulin Rapid, short, intermediate, and long-acting formulations.

 Newer insulins Insulin detemir, insulin glulisine, insulin degludec

 GLP-1 agonists Exenatide, liraglutide,albiglutide,lixisenatide,taspoglutide

 Amylin analogue Pramlintide

RECENT DRUGS

Sodium–glucose-cotransporter-2 (SGL2) inhibitors

Dapagliflozin, canagliflozin, ASP1941, LX4211, and BI10773

11β-hydroxysteroid-dehydrogenase-1 inhibitors

INCB13739 (200 mg) DUAL PPAR (γ +α) AGONIST

Aleglitazar Glucokinase activator Piragliatin, compound 14,

R1511, AZD1656, AZD6370, compound 6 Bile acid sequestrants Colesevelam

Anti-CD3 monoclonal antibody Otelixizumab, teplizumab Cannabinoid receptor-1 antagonists

Rimonabant Histamine H3 receptor agonist Proxyfan

Glucagon receptor antagonists Compound 1 (cpd 1)

Atherogenics antioxidant/vascular cell adhesion molecule-1

Succinobucol/AGI 1067

Recombinant human glutamic acid decarboxylase-65 (rhgad65) Vaccine, induces immunotolerization IL-1 antagonist

Anakinra Insulin action enhancers

Gip antagonists Sirtuins

Adipose tissue signals

In-vivo Screening Procedures For Anti-Diabetic Drugs

In-vivo Screening Procedures For Anti-Diabetic Drugs

In-vivo Screening Procedures For Anti-Diabetic Drugs

Preclinical testing of drugs in experimental animals or in vitro for their biological and toxic effects and potential clinical applications.

In-vivo Screening Procedures
1. Models For Insulin Dependent Diabetes Mellitus [IDDM]
2. Models For NIDDM
3 Models For Insulin Sensitivity and Insulin Like Activity

Animals Used For The Screening Of Anti-Diabetic Drug

Obese mouse
Diabetic mouse
Sand mouse [Psammomys obesus]
Spiny mouse [Acomys cahirinus]
BB rats
KK mouse
Yellow mouse
NOD mouse
Yellow KK mouse
New Zealand obese mouse
Tuco-tuco [clenomys talarum]- these are burrowing rodents from Argentina.
Chinese hamster [Cricetulus griseus]

Chemical Agents Capable Of Inducing Diabetes

A) Irreversible beta cytotoxic agents:
Alloxan
Streptozocin
Diphenyl thiocarbazine
Oxine-9- hydroxyquinolone
Vacor

B) Reversible beta cytotoxic agents

6- aminonicotinamide
l-asparginase
Cyanide
Cyproheptadine

C) Other agents
Anti insulin antibodies
Somatostatins
Catecholamines

In-vivo Screening Procedures For Anti-Diabetic Drugs

1. Models For Insulin Dependent Diabetes Mellitus [IDDM]
Alloxan induced diabetes
Alloxan: is a cyclic urea compound, which induces permanent diabetes.
It is a highly reactive molecule, which produces free radical damage to beta islet cells & causes cell death.
Dose: – In rats Alloxan at dose of 100 mg/kg produces diabetes.
In rabbits dose of 150 mg/kg infused through marginal ear vein produces diabetes in 70% of the animals.

PPT Anti Diabetic In vivo screening procedure antididabetic drugs
Procedure: –

Albino rats of either sex [150-200g] are injected with a single dose of alloxan monohydrate [100 mg/kg body weight] dissolved in normal saline by i.p. route.

Blood glucose levels show triphasic response with hyperglycemia for one hour followed by hypoglycemia that lasts for six hours & stable hyperglycemia after 48 hours.

Animals showing fasting blood glucose level above 140 mg/dl after 48 hour of alloxan administration are considered diabetic
For a period of six weeks, drug samples to be screened are administered orally
After six weeks of treatment, blood samples are collected from 8 hour fasting animals through a caudal vein
Serum is separated by centrifuge (3000 rpm) under cooling (2-4 °C) for ten minutes
The serum glucose level is estimated by glucose oxidase-peroxidase method [GOD-POD kit] using autoanalyser.

1.2 Streptozotocin induced diabetes

Streptozotocin: is a broad-spectrum antibiotic, which causes beta islet cell damage by free radical generation.
It induces diabetes in almost all species of animals excluding rabbits and guinea pigs.
Dose: – Diabetogenic dose: In Mice: 200mg/kg i.p
Beagle dogs: 15 mg/ kg i.v for three days.

Procedure: –
Streptozotocin [60 mg/kg body weight] is prepared in citrated buffer [ph 4.5]
Albino rats of either sex weighing 150-200 g are injected i.p with above solution
Animals showing fasting blood glucose levels > 140mg/dl after 48 hours of streptozotocin administration are considered diabetic.
· After six weeks of treatment blood samples are collected from 6 hr fasted animals through caudal vein
·Serum is separated by centrifuge (3000 rpm) under cooling (2-4 °C) for ten minutes
· Serum glucose level is estimated by glucose- peroxidase method [GOD-POD kit] using autoanalyser.

1.3 Virus induced diabetes

Principle: –
Viruses are one of the etiological agents for IDDM. They produce diabetes mellitus by infecting and destroying beta cells of pancreas.
Various human viruses used for inducing diabetes include RNA picornovirus, encephalomyocarditis [EMC-D], coxsackie B4 [CB-4].

Procedure: –
6-8 week old mice are inoculated by 0.1 ml of 1:50 dilutions of D-variant encephalomyocarditis [EMC] through i.p.

0.1ml of above dilution contains 50 PFU [ plaque forming units] of EMC virus.(mortality due to this concentration of virus is approximately 10-20%)
Less infecting variant produces a comparable damage by eliciting autoimmune reactivity to the beta cells.

· Infected animals are considered hyperglycemic if there non fasting levels exceed by 250mg/dl the levels of uninfected animals of the same strain.
· Drug samples to be screened are administered orally for a period of 6 weeks
· After 6 weeks of drug treatment, blood glucose estimation is done to determine the anti diabetic activity.

Thesis Title Template M Pharm B Pharmacy Projects PHD Format

Thesis Title Template M Pharm B Pharmacy Projects PHD Format

Here is the template format for M Pharmacy Project B Pharmacy PHD projects. Every one needs to design the first page I mean title of the thesis when we need to submit the project finally. So we pharmawiki team thought it would really HELPFUL FOR ALL THE M Pharmacy Project B Pharmacy PHD projects students to submit their thesis with ease.

—-M Pharmacy Project B Pharmacy PHD project Thesis:

All you need in this TITLE PAGE of this Thesis is a list of the below:

  • Title of the Project you have done
  •  thesis Submitted for the AWARD
  • of
  • Your Stream of Study
  • To
  • University Logo
  • University name
  • By
  • Your Name
  • Department Logo 
  • Department Name 
  • College Name 
  • University Name 
  • Address 
  • Pincode

Title of the Project:

Example :

The Matrix-Binding Domain of Microfibril-Associated Glycoprotein-1 Targets 

ACTIVE CONNECTIVE TISSUE GROWTH FACTOR TO A FIBROBLAST-PRODUCED EXTRACELLULAR MATRIX
TISSUE RECOMBINANTS TO STUDY EXTRACELLULAR MATRIX TARGETING TO BASEMENT MEMBRANES.

A STUDY OF DESIGNING NOVEL A2A ADENOSINE RECEPTOR ANTAGONIST-A COMPUTATIONAL APPROACH.

 Thesis Submitted for the AWARD of

Your Stream of Study

Example :

MASTER of PHarmacy

IN PARMACEUTICAL CHEMISTRY

University Logo

Example

Title page for thesis Submission M Pharmacy Project B Pharmacy PHD projects Title page for thesis Submission M Pharmacy Project B Pharmacy PHD projects

BY

Your Name

Example :

Purnima Robinson

Department Logo

Department Name

Example  Department of Pharmacy

College Name

University Name

Address

Pincode

Thesis Title Template M Pharm B Pharmacy Projects PHD Format

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pH Partition Hypothesis – Gastrointestinal #Absorption of Drugs

pH Partition Hypothesis Factors Affecting GastroIntestinal Absorption of Drugs

pH Partition Hypothesis is one of the PHYSICOCHEMICAL, PHARMACEUTICAL, AND BIOLOGICAL CONSIDERATIONS IN GIT ABSORPTION OF DRUGS. This can be understood clearly as a sub topic of pH Partition Hypothesis Factors Affecting GastroIntestinal Absorption of Drugs.

Explanation:

As we all know Drugs that are weakly acidic or weakly basic generally undergo ionization and their absorption can be explained by the drug’s pKa, lipophilicity, and GI pH.
In contrast to the capillary walls, cell membranes were able to act as effective barriers during the absorption of drugs. MH Jacobs in 1940 reported the cellular permeation characteristics of weakly electrolytic solutions designated the permeability of nonionic species quantitatively. After his studies, many studies followed and led to the hypothesis of pHpartition theory (Maza´k and Nosza´l, 2014). This theory compared the dissociation constant, lipophilicity, and pH with absorption. Knowledge of the exact ionization of the drug is important as the unionized form has greater lipophilicity than its ionized counterpart. pH partition hypothesis can be explained by the HendersonHasselbach equations. Check the image for the HendersonHasselbach equations for acids and HendersonHasselbach equations for bases.

For acids,
pH5pKa1log
ionized
unionized

pH partition hypothesis can be explained by the HendersonHasselbach equations as follows:

pH Partition Hypothesis Factors Affecting GastroIntestinal Absorption of Drugs

And for bases,
pH5pKa1log
unionized
ionized

Most of the absorption studies confirmed the accuracy of this hypothesis. However, there are certain limitations to it. These are related to the unstirred water layer, the microclimate
pH, and the mucous coat adjacent to the epithelial cells.

Note :

For drugs to cross the lipid membrane they need to have some solubility in the lipid membrane and to get dissolved in GIT they have to have aqueous solubility. Unionized forms can undergo passive diffusion to get transported as they has lipid solubility, but the ionized form is required for the solubility of the drug in the GIT. Drugs that are weakly acidic and weakly basic, generally undergo ionization (Yang et al., 2012).

Mostly drugs are developed as salts of weak bases or weak acids to have good solubility and absorption. These salt forms are ionizable and therefore their solubility is pH dependent. The following equations can be derived to understand the pH-dependent solubility of the drugs from the dissociation of monoprotonated conjugate acid from a base.

Top 10 Causes 4 Death || Deadly Diseases Causing Deaths Worldwide

Top 20 Causes 4 Death || Deadly Diseases Causing Deaths Worldwide

Deadly Diseases Causing Deaths Worldwide Daily As the world population is increasing in multifold the diseases affecting lives is even grosser. The foremost organization that keeps records of all the statistics regarding health, WHO, has given some estimation about the scenario as a whole. WHO says across worldwide, most people in wealthy countries would reasonably expect to die in older age. In low-income countries though, children aged under 5 years are the most at risk of dying. Let us see how the mortality rate of people has been affected in the recent past.

During the past decade, the deadly causes of death have been Ischaemic heart disease, stroke, chronic obstructive lung disease and lower respiratory infections including cancers. Heart disease is caused by a build-up of fatty deposits on the wall of the arteries, for other conditions such as high blood pressure or diabetes (Diabetes caused 1.6 million (2.8%) deaths in the last 5 years) responsible for nearly 9 million deaths every year. This disease is deadly that narrow down the patient’s arteries restricting blood and oxygen flow to the heart, potentially leading to a fatal heart attack. Non-deadly attacks cause chest pain known as angina, which can proceed with a heart attack. Lung disease, particularly lung cancer stands at top 5 of the 10 diseases being responsible for over 1.6 million deaths worldwide. Lung cancer is very common in smokers and is an aggressive and serious form of cancer accounting for 85% of cases. In China, it is the most common type of cancer along with Countries such as Spain and Hungary and India is also highly affected by the disease.

Chronic diseases have remained the top killers causing increasing numbers of deaths worldwide. TB remains a significant threat as one of the topmost in the world in which 1/3rd of the world’s population is infected. TB bacteria every year, causes over 9 million cases resulting in around 1.4 million deaths. Deaths due to Alzheimer and Dementias more than doubled in the last 20 years, making it the 7th leading cause of global deaths in recent times.

Seasonal flu kills 291,000 to 646,000 people worldwide each year, Healthy people can be infected by the influenza virus and transmit it to others. But young children, elderly people, pregnant women, and people with certain medical conditions are at greater risk of suffering serious complications from the flu. Various kind of Injuries continues to kill 5 million people each year including road traffic injuries. About 3700 lives each day are lost, among which three-quarters being males.

Another life-threatening disease is HIV+ causing AIDS is mostly spread worldwide. As a public health threat by 2030, countries need to live up to their commitment to end AIDS. In September 2015, it is a target included in the 2030 Agenda for Sustainable Development adopted by the United Nations General Assembly. This is an estimation to prevent almost 300 000 deaths per year. The HIV-related deaths are still unacceptably high and it poses an immediate challenge to reach the Fast-Track targets for 2020 that include reducing the number of people dying from HIV-related causes fewer than 500 000.

The outbreak of Covid-19, a coronavirus-caused illness that originated in Wuhan, China, and has since spread to most of the world, is one of the most serious public health crises in decades. The virus has spread far wider than Ebola did in 2014 and is in pandemic stage according to WHO. So far it has it the regions of the UK, USA, Korea, Japan, Iran, Italy and now India causing several deaths. If soon the measures not taken this would become the maximum cause of death rate throughout the world creating an epidemic.

Top 10 Causes of Death globallyTop 10 Causes of Death globally

 

 

Top 20 Causes 4 Death || Deadly Diseases Causing Deaths Worldwide

Top 20 Causes 4 Death || Deadly Diseases Causing Deaths Worldwide

 

Best First Aid Kit – Items Checklist Supplies Contents – Types of First Aid Kits PDF

Best First Aid Kit - Items Checklist Supplies Contents - Types of First Aid Kits PDF

Hello readers. Welcome to pharmawiki.in Today we have an article listing out items first aid kits, first aid kit band ,first aid kit checklist ,first aid kit contents ,first aid kit supplies, best first aid kit ,first aid kit list ,good first aid kit ,first aid kit music group , first aid kit requirements. In addition to these we provide detailed First aid manual with every minute detailed information regarding first aid. 

Types of First Aid Kits

Home First Aid Kits

Auto & Car First Aid Kits
Burn Care Kits
Kitchen First Aid Kits
Plastic First Aid Kits
Small First Aid Kits
First Aid Kit Refills

Recreation First Aid Kits

Medical Sea Pak & Marine Kits
Sports First Aid Kits
Empty Bags & Boxes
Sports Medicine Supplies
Professional First Aid Kits
CPR Kits
Metal First Aid Kits
First Responder Kits
Personal Protection Kits
ANSI First Aid Kits
Specialty Kits

First Aid Supplies

Airway Management
Bandages
Burn Care
CPR Masks & Shields
Hazmat & Bio Hazard
Medical Instruments
Gauze & Dressings
Hot & Cold Therapy
Medical Gloves
Medical Tape
Pain Relief
Ointments & Antiseptics
Unitized Medical Supplies
Defibrillators/AEDs
Emergency Survival Supplies
Home Healthcare Supplies
Over the Counter Medicine
EMS Supplies
Personal Care
Tourniquets
Vitamins & Minerals
Clearance
Tattoo Supplies
First Aid Kits & Bags Clearance

Portable Hospital First Aid Kit
(bag with supplies)

Portable Hospital First aid Kit has bag with supplies which contains everything from butterfly bandages to large trauma dressings, allowing you to treat a wide variety of first aid emergencies. Includes CPR Microshield.

Example for Supply Assortment Portable Hospital First aid Kit

50 Bandages 1″x3″
5 Bandages 2″x4″
5 Fingertip Bandages
5 Knuckle Bandages
5 Butterfly Bandages
2 Triangular Bandage 40″ x 40″
1 Elastic Bandage 3″
10 Gauze Pads 2″ x 2″
10 Gauze Pads 4″ x 4″
1 Roll Gauze 2″ x 4yds.
2 Roll Gauze 4″ x 4yds.
2 Combine Pads 5″ x 9″
1 Multi-Trauma Dressings
25 BZK Towelettes
4 Iodine Swab Sticks

Best First Aid Kit - Items Checklist Supplies Contents - Types of First Aid Kits PDF

GSA Contract
12 Triple Antibiotic Ointments
3 Hydrocortisone Creams
4 Burn Jels 1/8 oz.
6 Antimicrobial Hand Wipes
2 Cold Packs
1 Eyewash 4 oz.
3 Eye Pads
6 Cotton-Tip Applicators 3″, 2pk.
1 Tape 1″ x 10 yds.
1 Scissors, Paramedic
1 Splinter Forceps (tweezers)
1 Penlight, disposable
1 CPR Microshield
2 Bio-Waste Bags
6 Gloves
1 First Aid Guide

CONTENT OF A FIRST AID KIT

SMALL FIRST AID BOX

1 tube silver sulfadiazine ointment 15 g
10 band aid strips
1 roller bandage 5×5 cm
1 package absorbent sterilized cotton 15 g
1 scissor 7cm (sharp/blunt edge)
10 tablets paracetamol
1 plastic mouth-to-mouth resuscitator
1 triangular bandage (90 cm)
10 safety pins
1 adhesive plaster/tape
3-4 ice cream spoons to be used as splints of finger
2 ORS sachets

MEDIUM FIRST AID BOX – Items

10 sterilized finger dressings
10 sterilized foot and hand dressings
10 sterilized large dressings
1 sterilized extra-large dressings
2 sterilized first aid field dressings
2 sterilized shell dressings
4 sterilized small burn dressings
2 sterilized large burn dressings
50 adhesive dressing strips
4 roller bandages 5 cm (5 m)
2 roller bandages 7.5 cm (5 m)
6 triangular bandages (90 cm)
1 package gauze 7.5 cm
4 package sterilized absorbent cotton 25 g
6 sterilized eye pads (st John pattern)
1 spool adhesive plaster 2.5 cm (5 m)
1 tube sliver sulfadiazine skin ointment 15 g
1 bottle savlon, detol or catavelon 112 ml
2 surgical scissors 12.5 cm (sharp/blunt edge)
1 mouth-to-mouth resuscitator
3 inflatable arm splints
3 inflatable leg splints
1 torch (2 battery cells)
10 safety pins
3-4 ice cream spoons to be used as splints of finger
2 ORS sachets
1 writing pad and pen
1 record card in plastic cover
1 first aid leaflet form

LARGE FIRST AID BOX – Contents

18 sterilized finger dressings
24 sterilized foot and hand dressings
20 sterilized large dressings
2 sterilized extra-large dressing
4 sterilized first aid field dressings
6 sterilized shell dressings
6 sterilized small burn dressings
4 sterilized large burn dressings
100 adhesive dressing strips
6 roller bandages 5 cm (5 m)
6 roller bandages 7.5 cm (5 m)
12 triangular bandages (90 cm)
1 package gauze 7.5 cm
8 package sterilized absorbent cotton 25 g
6 sterilized eye pads (st John pattern)
2 spool adhesive plaster 2.5 cm (5 m)
1 tube sliver sulfadiazine skin ointment 15 g
1 bottle savlon, detol or catavelon 112 ml
2 surgical scissors 12.5 cm (sharp/blunt edge)
1 mouth-to-mouth resuscitator
3 inflatable arm splints
3 inflatable leg splints
3-4 ice cream spoons to be used as splints of finger
2 ORS sachets
2 torch (2 battery cells)
10 safety pins
1 writing pad and pen
1 record card in plastic cover
1 first aid leaflet form

FIRST MEDICAL RESPONDER FIRST AID KIT Supplies

1 torch powered by charging dynamo (inbuilt) with battery backup (preferred)
2 pair (latex) surgical gloves non-sterile size 6.5
2 pair (latex) surgical gloves non-sterile size 7.0
2 pair (latex) surgical gloves non-sterile size 7.5
1 bottle savlon 50 ml
2 4’ crepe bandage
2 6’ crepe bandage
5 triangular bandage (cotton)
4 compressed roller bandage non-sterile 5 cm by 5 m
4 compressed roller bandage non-sterile 10 cm by 5 m
4 compressed roller bandage non-sterile 15 cm by 5 m
2 rolls surgical cotton 100 g
25 adhesive bandaged (band aid) 2.5 by 5 cm
1 roll leucoplast tape or Micropore adhesive plaster 4”
6 sterile gauze 10 by 10 cm
6 sterile eye pads
5 sterile small finger dressing pads
5 sterile large finger dressing pads
4 pieces sterile paraffin gauze
1 tube silver sulfadiazine ointment
1 mouth to mouth resuscitator
1 set inflatable splints for arms and legs
2 small scissors (s/s)
1 package glucose powder 100 g
1 small forceps
1 medium forceps
1 large forceps
12 safety pins
1 small permanent marker pen (black)
1 pencil
1 first aid kit checklist
1 first aid pamphlet
1 small pocket diary.

#FilmCoated Tablets – Film-Coating Defects Flaw Cause Remedy

#FilmCoated Tablets - Film-Coating Defects Flaw Cause Remedy

#FilmCoated Tablets – Film-Coating Defects Flaw Cause Remedy

Wrinkling or blistering

Flaw: Film detaches from tablet surface, causing blister that can burst to form wrinkles.
Cause: Gases forming on tablet surface during coating; exacerbated by poor adhesion of film to tablet surface.
Remedy: Reduce drying air temperature.

Picking

Flaw: Areas of tablet surface are not covered by film coat.
Cause: Overwet tablets stick together and pull film off surface as they move apart.
Remedy: Decrease spraying rate. Increase drying temperature.

#FilmCoated Tablets - Film-Coating Defects Flaw Cause Remedy
#FilmCoated Tablets – Film-Coating Defects Flaw Cause Remedy

Pitting

Flaw: Holes appear on tablet surface.
Melting of lubricant on tablet surface. Most common with stearic acid.
Remedy: Decrease coating temperature to below melting point of lubricant. Substitute lubricant

Blooming

Flaw: Dulling of surface, normally after prolonged storage.
Migration of low-molecularweight components of film to tablet surface.
Remedy: Decrease temperature and length of drying process. Increase molecular weight of plasticizer.

Mottling

Flaw: Uneven color distribution in film.
Inadequate pigment dispersion. Color migration, a problem with dyes and lakes rather than pigments.
Remedy: Alter suspension preparation to ensure pigment aggregates are dispersed. Replace dyes with pigments.

Orange peel

Flaw: Film surface has a rough finish resembling orange peel. Film-coat droplets are too dry or too viscous to spread on tablet surface.
Remedy: Reduce solids content of coating suspension. Reduce drying temperature. Reduce viscosity of polymer.

Bridging

Flaw: Film forms a bridge over intagliations, leaving them indistinct. High internal stresses in film relieved by pulling the film off the Surface of the intagliation.
Remedy: Increase adhesion of coat to tablet by changing core formulation. Add plasticizer or increase plasticizer concentration. Alter geometry of intagliations.

Cracking, splitting, peeling

Flaw: The film cracks on the crown of the surface or splits on the tablet edge. Can be differentiated from picking by presence of loose film around the flaw.
High stresses in the film that cannot be relieved due to the strong Adhesion of the film to the tablet surface.
Remedy: Increase plasticizer concentration. Use stronger polymer.

#Heat Distribution – Autoclave Performance Qualification Protocol (PQP) Steam/Air Cycle

Heat distribution of an empty chamber: Thermocouples should be situated according to a specific predetermined pattern. Repeatability of temperature attainment and identification of the cold spot can be achieved if the tempera­ture range is ±15°C at all monitored locations. Heat-distribution studies can also be conducted as a function of variable airflow rates

Constraining the temperature range across the loaded chamber has the goal of assuring sterilization is attained across the load, without over-processing of the filled containers.

Performance Qualification Protocol (PQP) – Steam/Air Cycle- Heat distribution

Performance Qualification Protocol (PQP) for Steam/Air Cycle in the Production Steam Steriliser (Autoclave)

The Production Steam Steriliser (autoclave), shall be used for sterilising aseptically-filled vials of selected products. To qualify the performance of the Fedegari Steam Steriliser (Autoclave) as part of a change control qualification study (refer to CR-14- xxxx “Recommence Manufacture of xxxx Acid Injection 15 mg in 1 mL ) This Performance Qualification shall be limited to demonstrating consistency and efficacy of the steam/air sterilisation cycle, using 1mL water filled into 2 mL vials. Equivalence for xxx Injection 15 mg in 1 mL product, which has been aseptically filled into 2 mL vials, shall be demonstrated in the subsequent Process Validation Study (see PQ protocol kkk). This protocol has been prepared with reference to the following regulatory guidelines: The Performance Qualification study (PQP kkk ) for the autoclave equipment, included heat distribution studies for a porous load cycle only. This document shall include heat distribution studies for the steam/air sterilisation cycle, as part of the process development for the terminal sterilisation of filled vials. The objective of this Performance Qualification, is to verify that the sterilising autoclave consistently provides the required sterility assurance, when operated under normal conditions, using standard minimum and maximum loading patterns and the specified settings: The production cycle registered for Folic Acid product is 121.1 o C for fifteen (15) minutes, to provide a minimum Fo = 8 min. The standard loading patterns shall be as follows: Minimum load Six (6) trays 2 mL vials, 340 vials per tray, across two autoclave shelves Maximum Load Nine (9) trays 2 mL vials, 340 vials per tray, across three autoclave shelves A reduced cycle shall also be run, for the standard production load patterns, to demonstrate that sub-optimal conditions also yield an acceptable level of sterility assurance. This shall be achieved by changing the timetemperature combination for the standard production load patterns to 121.1 o C, for ten (10) minutes, which is 66% of the registered sterilising condition of 121.1o C for 15 minutes.

Process Description

Sterilisation shall be by the moist heat process, using saturated steam, where F0 > 8 DT (see below). A steam-air mixture is used to control chamber pressure and assist in pressure equalisation between chamber and vials, particularly during the cool-down phase. In-process controls for the sterilisation phase of the cycle shall be temperature TE1 in the liquid product and sterilisation phase hold time. Temperature (TE 8 on the auxilliary heating device) and chamber pressure (TP01) are also required to control heating and forced cooling phases of the cycle. For the purposes of the PQ, sterilisation phase temperature and hold time data shall be processed to demonstrate that the physical characteristics of the cycle in terms of accumulated lethality (Fphys) exceed the minimum cycle design criteria (Fo), where: Fo > 8 DT for DTref = D121.1oC = 1.0 minutes and Fphys = Δt ∑10(T-Tref)/z Reference: BP Appendix XVIII “Methods of Sterilisation” and registered particulars, where Fo > 8 min is required. Biological Indicators shall be selected, to demonstrate the survival probability of a non-sterile unit (PNSU) ≤ 10–6 for both the normal production cycle (F0 ≥ 15) and a reduced cycle (F0 ≥10).

Performance Qualification Tests

Tests to be conducted and acceptance criteria are defined in the attached Performance Qualification Test Sheets.
Tests to be performed:
1 Test Instrument Calibration
2 Vacuum Leak Rate Test
3 Heat Distribution Test (empty chamber temperature mapping)
4 Heat Distribution Test (loaded chamber temperature mapping)
5 Heat Penetration studies for:
Production cycle standard loads (121.1 o
C for 15 minutes, two consecutive cycles) and for “Reduced”
cycle standard loads (121.1 o
C for 10 minutes, one cycle)
6 Biological challenge testing for standard and reduced cycle loads

Click here for complete detail 

Performance Qualification Protocol (PQP) for Steam/Air Cycle in the Production Steam Steriliser (Autoclave)heat distribution Performance Qualification Protocol for Steam Air Cycle in the Production Steam Steriliser Autoclave

Protein Homonlogy Modelling #PPT PDF for Seminars for Students & Researchers

Protein Homology Modelling PPT PDF for students researchers scholars images

Protein Homology Modelling

 

 Objectives

 

–   Individual steps involved in calculating a protein homology model.

–   Identify suitable templates for modelling.

–   Outline the principles behind ab initio protein structure prediction.

–   Describe the differences between homology modelling and ab initio structure prediction.

–   Describe the major pitfalls in protein modelling.

 

Outline

§  Protein homology modelling

–   Individual steps

–   Caveats

–   Pitfalls

 

§  Ab initio protein structure prediction

–   Threading

–   True ab initio methods

 

How Is It Possible?

§  The structure of a protein is uniquely determined by its amino acid sequence
(but sequence is sometimes not enough):

–   prions

–   pH, ions, cofactors, chaperones

 

§  Structure is conserved much longer than sequence in evolution.

–   Structure > Function >> Sequence

Protein-Homology-Modelling-PPT-PDF-for-students-researchers-scholar download

How Often Can We Do It?

§  There are currently ~47000 structures in the PDB (but only ~4000 if you include only ones that are not more than 30% identical and have a resolution better than 3.0 Å).

 

§  An estimated 25% of all sequences can be modeled and structural information can be obtained for ~50%.

Worldwide Structural Genomics

§  Complete genomes

§  Signaling proteins

§  Disease-causing organisms

§  Model organisms

§  Membrane proteins

§  Protein-ligand interactions

 

Structural Genomics in North America

§   10 year $600 million project initiated in 2000, funded largely by NIH.

§   AIM: structural information on 10000 unique proteins (now 4-6000), so far 1000 have been determined.

§   Improve current techniques to reduce time (from months to days) and cost (from $100.000 to $20.000/structure).

§   9 research centers currently funded (2005), targets are from model and disease-causing organisms (a separate project on TB proteins).

Protein Homology Modelling PPT PDF for students researchers scholars

Homology Modeling for Structural Genomics

How Well Can We Do It?

How Is It Done?

§  Identify template(s) – initial alignment

§  Improve alignment

§  Backbone generation

§  Loop modelling

§  Side chains

§  Refinement

§  Validation ß

 

Template Identification

§  Search with sequence

–  Blast

–  Psi-Blast

–  Fold recognition methods

 

§  Use biological information

 

§  Functional annotation in databases

 

§  Active site/motifs

Alignment

 

 

Improving the Alignment

Template Quality

§  Selecting the best template is crucial!

§  The best template may not be the one with the highest % id (best p-value…)

–   Template 1: 93% id, 3.5 Å resolution L

–   Template 2: 90% id, 1.5 Å resolution J

 

Evaluation of NMR Structures

What regions in the structure are most well-defined?

 

Template Quality – Ramachandran Plot

Backbone Generation

 

§  Generate the backbone coordinates from the template for the aligned regions.

 

§  Several programs can do this, most of the groups at CASP6 use Modeller:

 

http://salilab.org/modeller/modeller.html

 

Loop Modelling

§   Knowledge based:

–    Searches PDB for fragments that match the sequence to be modelled (Levitt, Holm, Baker etc.).

 

§   Energy based:

–    Uses an energy function to evaluate the quality of the loop and minimizes this function by Monte Carlo (sampling) or molecular dynamics (MD) techniques.

 

§   Combination

Loops – the Rosetta Method

 

§  Find fragments (10 per amino acid) with the same sequence and secondary structure profile as the query sequence.

 

§  Combine them using a Monte Carlo scheme to build the loop.

                                                 

                                                       David Baker et al.

Side Chains

 

 

§  If the seq. ID is high, the networks of side chain contacts may be conserved, and keeping the side chain rotamers from the template may be better than predicting new ones.

 

Predicting Side Chain Conformations

§  Side chain rotamers are dependent on backbone conformation.

 

§  Most successful method in CASP6 was SCWRL by Dunbrack et al.:

–   Graph-theory knowledge based method to solve the combinatorial problem of side chain modelling.

 

http://dunbrack.fccc.edu/SCWRL3.php

Side Chains – Accuracy

§  Prediction accuracy is high for buried residues, but much lower for surface residues

–   Experimental reasons:
side chains at the surface are more flexible.

–   Theoretical reasons:
much easier to handle hydrophobic packing in the core than the electrostatic interactions, including H-bonds to waters.

 

Refinement

§  Energy minimization

§  Molecular dynamics

 

–   Big errors like atom clashes can be removed, but force fields are not perfect and small errors will also be introduced – keep minimization to a minimum or matters will only get worse.

Error Recovery

§  If errors are introduced in the model, they normally can NOT be recovered at a later step

–   The alignment can not make up for a bad choice of template.

–   Loop modeling can not make up for a poor alignment.

§  If errors are discovered, the step where they were introduced should be redone.

Validation

§   Most programs will get the bond lengths and angles right.

§   The Ramachandran plot of the model usually looks pretty much like the Ramachandran plot of the template (so select a high quality template).

§   Inside/outside distributions of polar and apolar residues can be useful.

§   Biological/biochemical data

–    Active site residues

–    Modification sites

–    Interaction sites

Validation – ProQ Server

§  ProQ is a neural network based predictor that based on a number of structural features predicts the quality of a protein model.

 

§  ProQ is optimized to find correct models in contrast to other methods which are optimized to find native structures.

Structure Validation

§  ProCheck

http://www.biochem.ucl.ac.uk/~roman/procheck/procheck.html

 

§  WhatIf server

http://swift.cmbi.kun.nl/WIWWWI/

Homology Modelling Servers

 

§  Eva-CM performs continuous and automated analysis of comparative protein structure modeling servers

§  A current list of the best performing servers can be found at:

 

http://cubic.bioc.columbia.edu/eva/doc/intro_cm.html

 

Summary – Homology Modelling

 

§  Successful homology modelling depends on the following:

–   Template quality

–   Alignment (add biological information)

–   Modelling program/procedure (use more than one)

 

§  Always validate your final model!

Fold Recognition and Ab Initio Protein Structure Prediction

Outline

§  Threading and pair potentials

§  Ab initio methods

§  Human intervention (what kind of knowledge can be used for alignment and selection of templates?)

§  Meta-servers (the principle, 3d jury)

§  Summary of take-home messages

Threading and Pair Potentials

§   Compares a given sequence against known structures (folds).

§   By using potentials that describe tendencies observed in known protein structures.

Potentials of Mean Force

Threading Methods Today

§   Problem: No protein is average

§   Interactions in proteins cannot only be described by pairs of amino acids

§   The information in the potentials is partly captured with sequence profiles

§   Today mostly used in HYBRID approaches in combination with profile-profile based methods

§   Potentials can be used to score models based on different templates or alignments

Ab Initio Methods

 

§   Aim is to find the fold of native protein by simulating the biological process of protein folding.

§   A VERY DIFFICULT task because a protein chain can fold into millions of different conformations.

§   Use it only when no detectable homologues are available.

§   Methods can also be useful for fold recognition in cases of extremely low homology (e.g. convergent evolution).

Fragment-based Ab Initio Modelling

§  Rosetta method of the Baker group:

–   Submit sequence to a number of secondary structure predictors.

–   Compare fragments of 3 and 9 residues to library from know structures.

–   Link fragments together.

–   Use energy minimization techniques (Monte Carlo optimization) to calculate tertiary structure.

Potentials for Finding Good Models

 

§   Use of energy potentials for scoring and computing models.

§   Potentials should make models more “native-like”.

§   These can be based on contact potentials, solvation potentials, Van der Waals repulsion and attractive forces, hydrogen bond potentials.

§   Globularity/radius of gyration (ab initio).

Problems with Empirical Potentials

Human Intervention

§   The best methods use maximum knowledge of query proteins.

 

 

§   Specialists can help to find a correct template and correct alignments.

Meta-Servers

§  Democratic modeling

–   The highest score hit is often wrong.

–   Many prediction methods have the correct fold among the top 10-20 hits.

–   If many different prediction methods all have some fold among the top hits, this fold is probably correct.

 

Example of a Meta-Server

§      3DJury http://bioinfo.pl/meta/

 

–             Inspired by Ab initio modeling methods

•             Average of frequently obtained low energy structures is often closer to the native structure than the lowest energy structure

–             Find most abundant high scoring model in a list of prediction from several predictors

•             Use output from a set of servers

•             Superimpose all pairs of structures

•             Similarity score  based on # of Cα pairs within 3.5Å

–             Similar methods developed by A. Elofsson (Pcons) and D. Fischer (3D shotgun).

3DJury

§  Because it is a meta-server it can be slow.

§  If queue is too long some servers are skipped.

§  Output is only Cα coordinates.

§  What to do with the rest of the structure?

§  Use e.g. maxsprout server to build sidechains and backbone atoms.

http://www.ebi.ac.uk/maxsprout/

Summary – Ab Initio Methods

 

§   Hybrid methods using both threading methods and profile-profile alignments are the best.

§   Use only Ab initio methods if necessary and know that the quality is really low!

§   Try to use as much knowledge as possible for alignment and template selections in difficult cases.

§   Use meta-servers when you can.

Protein Homology Modelling

Thomas Blicher

Center for Biological Sequence Analysis

Learning Objectives

After this lesson you should be able to:

–   Explain the individual steps involved in calculating a protein homology model.

–   Identify suitable templates for modelling.

–   Outline the principles behind ab initio protein structure prediction.

–   Describe the differences between homology modelling and ab initio structure prediction.

–   Describe the major pitfalls in protein modelling.

 

Outline

§  Protein homology modelling

–   Individual steps

–   Caveats

–   Pitfalls

 

§  Ab initio protein structure prediction

–   Threading

–   True ab initio methods

 

How Is It Possible?

§  The structure of a protein is uniquely determined by its amino acid sequence
(but sequence is sometimes not enough):

–   prions

–   pH, ions, cofactors, chaperones

 

§  Structure is conserved much longer than sequence in evolution.

–   Structure > Function >> Sequence

 

How Often Can We Do It?

§  There are currently ~47000 structures in the PDB (but only ~4000 if you include only ones that are not more than 30% identical and have a resolution better than 3.0 Å).

 

§  An estimated 25% of all sequences can be modeled and structural information can be obtained for ~50%.

Worldwide Structural Genomics

§  Complete genomes

§  Signaling proteins

§  Disease-causing organisms

§  Model organisms

§  Membrane proteins

§  Protein-ligand interactions

 

Structural Genomics in North America

§   10 year $600 million project initiated in 2000, funded largely by NIH.

§   AIM: structural information on 10000 unique proteins (now 4-6000), so far 1000 have been determined.

§   Improve current techniques to reduce time (from months to days) and cost (from $100.000 to $20.000/structure).

§   9 research centers currently funded (2005), targets are from model and disease-causing organisms (a separate project on TB proteins).

Homology Modeling for Structural Genomics

How Well Can We Do It?

How Is It Done?

§  Identify template(s) – initial alignment

§  Improve alignment

§  Backbone generation

§  Loop modelling

§  Side chains

§  Refinement

§  Validation ß

 

Template Identification

§  Search with sequence

–  Blast

–  Psi-Blast

–  Fold recognition methods

 

§  Use biological information

 

§  Functional annotation in databases

 

§  Active site/motifs

Alignment

 

 

Improving the Alignment

Template Quality

§  Selecting the best template is crucial!

§  The best template may not be the one with the highest % id (best p-value…)

–   Template 1: 93% id, 3.5 Å resolution L

–   Template 2: 90% id, 1.5 Å resolution J

 

Evaluation of NMR Structures

What regions in the structure are most well-defined?

 

Template Quality – Ramachandran Plot

Backbone Generation

 

§  Generate the backbone coordinates from the template for the aligned regions.

 

§  Several programs can do this, most of the groups at CASP6 use Modeller:

 

http://salilab.org/modeller/modeller.html

 

Loop Modelling

§   Knowledge based:

–    Searches PDB for fragments that match the sequence to be modelled (Levitt, Holm, Baker etc.).

 

§   Energy based:

–    Uses an energy function to evaluate the quality of the loop and minimizes this function by Monte Carlo (sampling) or molecular dynamics (MD) techniques.

 

§   Combination

Loops – the Rosetta Method

 

§  Find fragments (10 per amino acid) with the same sequence and secondary structure profile as the query sequence.

 

§  Combine them using a Monte Carlo scheme to build the loop.

                                                 

                                                       David Baker et al.

Side Chains

 

 

§  If the seq. ID is high, the networks of side chain contacts may be conserved, and keeping the side chain rotamers from the template may be better than predicting new ones.

 

Predicting Side Chain Conformations

§  Side chain rotamers are dependent on backbone conformation.

 

§  Most successful method in CASP6 was SCWRL by Dunbrack et al.:

–   Graph-theory knowledge based method to solve the combinatorial problem of side chain modelling.

 

http://dunbrack.fccc.edu/SCWRL3.php

Side Chains – Accuracy

§  Prediction accuracy is high for buried residues, but much lower for surface residues

–   Experimental reasons:
side chains at the surface are more flexible.

–   Theoretical reasons:
much easier to handle hydrophobic packing in the core than the electrostatic interactions, including H-bonds to waters.

 

Refinement

§  Energy minimization

§  Molecular dynamics

 

–   Big errors like atom clashes can be removed, but force fields are not perfect and small errors will also be introduced – keep minimization to a minimum or matters will only get worse.

Error Recovery

§  If errors are introduced in the model, they normally can NOT be recovered at a later step

–   The alignment can not make up for a bad choice of template.

–   Loop modeling can not make up for a poor alignment.

§  If errors are discovered, the step where they were introduced should be redone.

Validation

§   Most programs will get the bond lengths and angles right.

§   The Ramachandran plot of the model usually looks pretty much like the Ramachandran plot of the template (so select a high quality template).

§   Inside/outside distributions of polar and apolar residues can be useful.

§   Biological/biochemical data

–    Active site residues

–    Modification sites

–    Interaction sites

Validation – ProQ Server

§  ProQ is a neural network based predictor that based on a number of structural features predicts the quality of a protein model.

 

§  ProQ is optimized to find correct models in contrast to other methods which are optimized to find native structures.

Structure Validation

§  ProCheck

http://www.biochem.ucl.ac.uk/~roman/procheck/procheck.html

 

§  WhatIf server

http://swift.cmbi.kun.nl/WIWWWI/

Homology Modelling Servers

 

§  Eva-CM performs continuous and automated analysis of comparative protein structure modeling servers

§  A current list of the best performing servers can be found at:

 

http://cubic.bioc.columbia.edu/eva/doc/intro_cm.html

 

Summary – Homology Modelling

 

§  Successful homology modelling depends on the following:

–   Template quality

–   Alignment (add biological information)

–   Modelling program/procedure (use more than one)

 

§  Always validate your final model!

Fold Recognition and Ab Initio Protein Structure Prediction

Outline

§  Threading and pair potentials

§  Ab initio methods

§  Human intervention (what kind of knowledge can be used for alignment and selection of templates?)

§  Meta-servers (the principle, 3d jury)

§  Summary of take-home messages

Threading and Pair Potentials

§   Compares a given sequence against known structures (folds).

§   By using potentials that describe tendencies observed in known protein structures.

Potentials of Mean Force

Threading Methods Today

§   Problem: No protein is average

§   Interactions in proteins cannot only be described by pairs of amino acids

§   The information in the potentials is partly captured with sequence profiles

§   Today mostly used in HYBRID approaches in combination with profile-profile based methods

§   Potentials can be used to score models based on different templates or alignments

Ab Initio Methods

 

§   Aim is to find the fold of native protein by simulating the biological process of protein folding.

§   A VERY DIFFICULT task because a protein chain can fold into millions of different conformations.

§   Use it only when no detectable homologues are available.

§   Methods can also be useful for fold recognition in cases of extremely low homology (e.g. convergent evolution).

Fragment-based Ab Initio Modelling

§  Rosetta method of the Baker group:

–   Submit sequence to a number of secondary structure predictors.

–   Compare fragments of 3 and 9 residues to library from know structures.

–   Link fragments together.

–   Use energy minimization techniques (Monte Carlo optimization) to calculate tertiary structure.

Potentials for Finding Good Models

 

§   Use of energy potentials for scoring and computing models.

§   Potentials should make models more “native-like”.

§   These can be based on contact potentials, solvation potentials, Van der Waals repulsion and attractive forces, hydrogen bond potentials.

§   Globularity/radius of gyration (ab initio).

Problems with Empirical Potentials

Human Intervention

§   The best methods use maximum knowledge of query proteins.

 

 

§   Specialists can help to find a correct template and correct alignments.

Meta-Servers

§  Democratic modeling

–   The highest score hit is often wrong.

–   Many prediction methods have the correct fold among the top 10-20 hits.

–   If many different prediction methods all have some fold among the top hits, this fold is probably correct.

 

Example of a Meta-Server

§      3DJury http://bioinfo.pl/meta/

 

–             Inspired by Ab initio modeling methods

•             Average of frequently obtained low energy structures is often closer to the native structure than the lowest energy structure

–             Find most abundant high scoring model in a list of prediction from several predictors

•             Use output from a set of servers

•             Superimpose all pairs of structures

•             Similarity score  based on # of Cα pairs within 3.5Å

–             Similar methods developed by A. Elofsson (Pcons) and D. Fischer (3D shotgun).

3DJury

§  Because it is a meta-server it can be slow.

§  If queue is too long some servers are skipped.

§  Output is only Cα coordinates.

§  What to do with the rest of the structure?

§  Use e.g. maxsprout server to build sidechains and backbone atoms.

http://www.ebi.ac.uk/maxsprout/

Summary – Ab Initio Methods

 

§   Hybrid methods using both threading methods and profile-profile alignments are the best.

§   Use only Ab initio methods if necessary and know that the quality is really low!

§   Try to use as much knowledge as possible for alignment and template selections in difficult cases.

§   Use meta-servers when you can.