Shandong Taibang Biological Products Co. Ltd.

Human parvovirus B19 (B19V) is a common contaminant found in plasma pools and plasma derivatives. Previous studies were mainly focused on limited aspects, further assessment of prevalence of B19V DNA and antibodies in plasma donors, the contamination of B19V in pooled plasma and plasma derivatives should be performed in China.

Individual plasma donors' samples from four provinces and pooled plasma from four Chinese blood product manufacturers were collected and screened using B19V DNA diagnostic kits between October 2018 and May 2020. The positive samples were investigated for the seroprevalence of B19V antibodies and subjected to sequence analysis and alignment for phylogenetic studies. Moreover, 11 plasma donors who were B19V DNA-positive at their first testing were also followed during the later donation period. Additionally, 400 plasma pools and 20 batches of plasma derivatives produced by pooled plasma with a viral load of B19V DNA exceeding 10⁴IU/mL were also collected and tested for B19V DNA and antibodies.

To comprehensively and systematically determine the frequency and viral load of B19V DNA in plasma donors, pooled plasma, and plasma derivatives from four Chinese blood product manufacturers.

A total of 17,187 plasma donors were analyzed and 44 (0.26%) specimens were found positive for B19V DNA. The quantitative DNA levels ranged from 1.01 × 10¹ to 5.09 × 10¹² IU/mL. Forty-four DNA-positive specimens were also investigated for the seroprevalence of B19V antibodies, 75.0% and 2.3% of which were seropositive for B19V IgG and IgM antibodies, respectively. The phylogenic analyses showed that the prevalent genotypes in the four provinces' plasma donors belonged to B19V Genotype 1. Eleven individual plasma donors who were B19V DNA-positive at the first donation were then followed for a period, and in general, the DNA levels of B19V gradually decreased. Moreover, 64.8% (259/400) of the pooled plasma was contaminated by B19V, with concentrations of 1.05 × 10⁰-3.36 × 10⁹IU/mL. Approximately 72.6% of the DNA-positive plasma pools were only moderately contaminated (<10⁴ IU/mL), while 27.4% contained >10⁴ IU/mL. Twenty batches of plasma derivatives produced by pooled plasma with a viral load of B19V DNA exceeding 10⁴IU/mL were also tested. B19V was detected in 5/5 PCC samples and 5/5 factor VIII samples but was not found in the intravenous immune globulin and albumin samples.

The contamination of B19V in pooled plasma and plasma-derived clotting factor concentrates is serious. Whether B19V nucleic acid testing (NAT) screening of plasma and plasma derivatives is launched in China, blood product manufacturers should spontaneously perform B19V NAT screening in plasma donors and mini-pool plasma. These measures can ensure that samples with high titer B19V DNA are discarded in order to prevent and control this transfusion transmitted virus.

For the modeling of near infrared spectroscopy (NIRS), the accuracy of the basic data, the stability of the spectra and the optimality of variables selection method were the important factors. In this paper, a novel optimization strategy for NIRS modeling was proposed, which was formed by data mean and ratio of absorbance to concentration (RATC) methods. The data mean method was aim to obtain accurate basic data and stable spectra, the RATC method was aim to select the optimal variables and compared with other variables selection methods (FiPLS, BiPLS, CC, UVE). The experimental subject was raw human plasma, with this novel optimization strategy, the predictive capability of NIRS model of its total protein (TP) content had been improved. At the same time, the public NIRS testing data (water, protein, oil, starch of corn and octane of gasoline) were used to verify the proposed variables selection method, and the predictive capability of these models of different parameters were also improved. To some extent, the optimization strategy of NIRS modeling provided theoretical supports for the development of protein content analyzer of NIRS and the quick determination of parameters of biologics and other materials.

Human albumin (HA) is a very important blood product which requires strict quality control strategy. Acid precipitation is a key step which has a great effect on the quality of final product. Therefore, a new method based on quality by design (QbD) was proposed to investigate the feasibility of realizing online quality control with the help of near infrared spectroscopy (NIRS) and chemometrics. The pH value is the critical process parameter (CPP) in acid precipitation process, which is used as the end-point indicator. Six batches, a total of 74 samples of acid precipitation process, were simulated in our lab. Four batches were selected randomly as calibration set and remaining two batches as validation set. Then, the analysis based on material information and three different variable selection methods, including interval partial least squares regression (iPLS), competitive adaptive reweighted sampling (CARS) and correlation coefficient (CC) were compared for eliminating irrelevant variables. Finally, iPLS was used for variables selection. The quantitative model was built up by partial least squares regression (PLSR). The values of determination coefficients ([Formula: see text] and [Formula: see text]), root mean squares error of prediction (RMSEP), root mean squares error of calibration (RMSEC) and root mean squared error of cross validation (RMSECV) were 0.969, 0.953, 0.0496, 0.0695 and 0.0826, respectively. The paired [Formula: see text] test and repeatability test showed that the model had good prediction ability and stability. The results indicated that PLSR model could give accurate measurement of the pH value.